From a4e6e78fe72e335887000302d605040d48bb579f Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Thu, 11 Jun 2026 01:31:31 -0400
Subject: [PATCH 1/3] feat(adapters): explore CTE/model view toggle +
 tests.html unit-test viewer via shared test-card partial (#102)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

dag.html gains a two-arm view toggle: the lineage view (boot) and the
highlighted model's CTE DAG, rendered by the same vendored Cytoscape +
dagre engine (templates/explore-cte.js). The carrier's new cte_dags map
ships one DagPayload per CTE-bearing compiled model — the exact
role-classified, join-typed graph the report renders (build_payload
reuse seam, parsed once). An uncompiled model ships no entry and renders
the labeled fail-open degraded view, never an error; PreflightError
stays four variants. The lineage instance is never rebuilt, so its
pan/zoom/highlight persist across toggles (local state, same page).

tests.html now serves the unit-test viewer through a SHARED askama
partial (templates/partials/test-card.html) extracted from report.html
output-preservingly (the report goldens stay byte-identical) and filled
client-side by templates/explore-tests.js from the embedded
cute-dbt-data payload — no jQuery, no DataTables, no graph engine on
the page; createElement+textContent only.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
---
 examples/explore/dag.html         | 330 +++++++++++++++++++++++++-
 examples/explore/tests.html       | 372 ++++++++++++++++++++++++++++--
 src/adapters/asset_embed.rs       |  76 ++++++
 src/adapters/explore.rs           | 212 ++++++++++++++++-
 src/adapters/render.rs            |   6 +-
 templates/explore-cte.js          | 274 ++++++++++++++++++++++
 templates/explore-dag.html        |  55 ++++-
 templates/explore-lineage.js      |  12 +
 templates/explore-tests.html      |  62 ++++-
 templates/explore-tests.js        | 267 +++++++++++++++++++++
 templates/partials/test-card.html |  39 ++++
 templates/report.html             |  48 +---
 12 files changed, 1682 insertions(+), 71 deletions(-)
 create mode 100644 templates/explore-cte.js
 create mode 100644 templates/explore-tests.js
 create mode 100644 templates/partials/test-card.html

diff --git a/examples/explore/dag.html b/examples/explore/dag.html
index e0c1b1fa..a88973c9 100644
--- a/examples/explore/dag.html
+++ b/examples/explore/dag.html
@@ -256,6 +256,21 @@
 .lineage-legend { color: #555; font-size: 0.85rem; margin-top: 0.5rem; }
 .lineage-legend .legend-chip { display: inline-block; padding: 0 0.4rem; border: 1.5px solid #0072B2; border-radius: 4px; background: #e8f1f8; color: #1c1c1f; }
 .lineage-legend .legend-chip.notcompiled { border-color: #b07400; border-style: dashed; background: #f4f4f5; }
+/* cute-dbt#102 — the CTE ⇄ model view toggle + the CTE view host. */
+.view-toggle { display: inline-flex; border: 1px solid #c5c5cc; border-radius: 6px; overflow: hidden; }
+.view-toggle button { border: none; border-radius: 0; margin: 0; background: #fff; color: #1c1c1f; padding: 0.25rem 0.7rem; font-size: 0.85rem; cursor: pointer; }
+.view-toggle button + button { border-left: 1px solid #c5c5cc; }
+.view-toggle button.is-active { background: #e8f1f8; font-weight: 600; }
+.view-toggle button:disabled { color: #999; background: #f4f4f5; cursor: not-allowed; }
+.cte-canvas { height: min(70vh, 40rem); border: 1px solid #c5c5cc; border-radius: 6px; background: #fcfcfd; }
+.cte-canvas:focus { outline: 2px solid #0072B2; outline-offset: 2px; }
+.cte-view-title { color: #555; font-size: 0.9rem; margin: 0 0 0.4rem; }
+.cte-degraded, .cte-view-empty { color: #555; font-style: italic; }
+.cte-legend { color: #555; font-size: 0.85rem; margin-top: 0.5rem; }
+.cte-legend .legend-chip { display: inline-block; padding: 0 0.4rem; border-radius: 4px; color: #1c1c1f; }
+.cte-legend .legend-chip.final { border: 1.5px solid #0072B2; background: #e8f1f8; }
+.cte-legend .legend-chip.import { border: 1.5px solid #1f8a5b; background: #eef7ee; }
+.cte-legend .legend-chip.transform { border: 1.5px solid #6b6b76; background: #f4f4f5; }
 </style>
 </head>
 <body>
@@ -279,9 +294,16 @@ <h1>Model lineage</h1>
       <ul class="lineage-search-results" id="lineage-search-results" role="listbox"
           aria-label="Matching models" hidden></ul>
     </div>
-    <p class="lineage-hint">click or search-select highlights a model&rsquo;s lineage &middot; <kbd>Space</kbd> commits focus on the highlighted model</p>
+    
+    <div class="view-toggle" role="group" aria-label="Graph view">
+      <button type="button" data-view="lineage" class="is-active" aria-pressed="true">Model lineage</button>
+      <button type="button" data-view="cte" aria-pressed="false" disabled>CTE view</button>
+    </div>
+    <p class="lineage-hint">click or search-select highlights a model&rsquo;s lineage &middot; <kbd>Space</kbd> commits focus &middot; a highlighted model unlocks its CTE view</p>
   </div>
   
+  <div class="lineage-view">
+  
   <div class="lineage-canvas" tabindex="0" aria-label="Interactive model lineage graph"></div>
   <p class="lineage-empty" hidden>No models in this manifest.</p>
   <div class="lineage-legend">
@@ -289,9 +311,23 @@ <h1>Model lineage</h1>
     <span class="legend-chip notcompiled">not compiled</span>
     &mdash; a dashed node has no compiled SQL in this manifest (<code>dbt parse</code>); run <code>dbt compile</code> to fill it in. The explorer renders it anyway (fail-open).
   </div>
+  </div>
+  
+  <div class="cte-view" hidden>
+    <p class="cte-view-title">CTE DAG &mdash; <code class="cte-view-model"></code></p>
+    <div class="cte-canvas" tabindex="0" aria-label="CTE dependency DAG"></div>
+    <p class="cte-degraded" hidden></p>
+    <p class="cte-view-empty" hidden>No CTE DAG available &mdash; this model&rsquo;s compiled SQL has no CTE structure.</p>
+    <div class="cte-legend">
+      <span class="legend-chip final">final select</span>
+      <span class="legend-chip import">import CTE</span>
+      <span class="legend-chip transform">transform CTE</span>
+      &mdash; edges are labeled with their join type.
+    </div>
+  </div>
 </section>
 
-<script type="application/json" id="explore-dag-data">{"nodes":[{"id":"model.healthcare_analytics.dim_conditions","name":"dim_conditions","not_compiled":false},{"id":"model.healthcare_analytics.dim_date","name":"dim_date","not_compiled":false},{"id":"model.healthcare_analytics.dim_organizations","name":"dim_organizations","not_compiled":false},{"id":"model.healthcare_analytics.dim_patients","name":"dim_patients","not_compiled":false},{"id":"model.healthcare_analytics.dim_payers","name":"dim_payers","not_compiled":false},{"id":"model.healthcare_analytics.dim_providers","name":"dim_providers","not_compiled":false},{"id":"model.healthcare_analytics.fct_clinical_events","name":"fct_clinical_events","not_compiled":false},{"id":"model.healthcare_analytics.fct_condition_cohorts","name":"fct_condition_cohorts","not_compiled":false},{"id":"model.healthcare_analytics.fct_cost_analysis","name":"fct_cost_analysis","not_compiled":false},{"id":"model.healthcare_analytics.fct_encounters","name":"fct_encounters","not_compiled":false},{"id":"model.healthcare_analytics.fct_encounters_incremental","name":"fct_encounters_incremental","not_compiled":false},{"id":"model.healthcare_analytics.fct_encounters_monthly","name":"fct_encounters_monthly","not_compiled":false},{"id":"model.healthcare_analytics.fct_encounters_yearly","name":"fct_encounters_yearly","not_compiled":false},{"id":"model.healthcare_analytics.fct_patient_summary","name":"fct_patient_summary","not_compiled":false},{"id":"model.healthcare_analytics.fct_provider_metrics","name":"fct_provider_metrics","not_compiled":false},{"id":"model.healthcare_analytics.int_dq_quarantine__encounters","name":"int_dq_quarantine__encounters","not_compiled":false},{"id":"model.healthcare_analytics.int_dq_quarantine__medications","name":"int_dq_quarantine__medications","not_compiled":false},{"id":"model.healthcare_analytics.int_encounters__enriched","name":"int_encounters__enriched","not_compiled":false},{"id":"model.healthcare_analytics.int_patients__with_conditions","name":"int_patients__with_conditions","not_compiled":false},{"id":"model.healthcare_analytics.mart_date_state_grid","name":"mart_date_state_grid","not_compiled":false},{"id":"model.healthcare_analytics.mart_dq_summary","name":"mart_dq_summary","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__conditions","name":"stg_synthea__conditions","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__encounters","name":"stg_synthea__encounters","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__medications","name":"stg_synthea__medications","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__observations","name":"stg_synthea__observations","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__organizations","name":"stg_synthea__organizations","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__patients","name":"stg_synthea__patients","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__payers","name":"stg_synthea__payers","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__procedures","name":"stg_synthea__procedures","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__providers","name":"stg_synthea__providers","not_compiled":false},{"id":"model.healthcare_analytics.v_encounter_summary","name":"v_encounter_summary","not_compiled":false},{"id":"model.healthcare_analytics.v_patient_current_conditions","name":"v_patient_current_conditions","not_compiled":false},{"id":"model.healthcare_analytics.v_provider_active_patients","name":"v_provider_active_patients","not_compiled":false}],"edges":[{"from":"model.healthcare_analytics.dim_conditions","to":"model.healthcare_analytics.fct_condition_cohorts"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_cost_analysis"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_encounters_monthly"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_encounters_yearly"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_patient_summary"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_provider_metrics"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.mart_date_state_grid"},{"from":"model.healthcare_analytics.dim_organizations","to":"model.healthcare_analytics.dim_providers"},{"from":"model.healthcare_analytics.dim_organizations","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_organizations","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.fct_condition_cohorts"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.int_patients__with_conditions"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.dim_payers","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_payers","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.dim_providers","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_providers","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.dim_providers","to":"model.healthcare_analytics.v_provider_active_patients"},{"from":"model.healthcare_analytics.fct_condition_cohorts","to":"model.healthcare_analytics.v_patient_current_conditions"},{"from":"model.healthcare_analytics.fct_condition_cohorts","to":"model.healthcare_analytics.v_provider_active_patients"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_cost_analysis"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_encounters_monthly"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_encounters_yearly"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_patient_summary"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_provider_metrics"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.int_encounters__enriched"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.v_provider_active_patients"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.dim_conditions"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.fct_condition_cohorts"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.fct_patient_summary"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.int_encounters__enriched"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.int_patients__with_conditions"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.fct_encounters_incremental"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.int_dq_quarantine__encounters"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.mart_dq_summary"},{"from":"model.healthcare_analytics.stg_synthea__medications","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.stg_synthea__medications","to":"model.healthcare_analytics.int_dq_quarantine__medications"},{"from":"model.healthcare_analytics.stg_synthea__medications","to":"model.healthcare_analytics.int_encounters__enriched"},{"from":"model.healthcare_analytics.stg_synthea__medications","to":"model.healthcare_analytics.mart_dq_summary"},{"from":"model.healthcare_analytics.stg_synthea__organizations","to":"model.healthcare_analytics.dim_organizations"},{"from":"model.healthcare_analytics.stg_synthea__patients","to":"model.healthcare_analytics.dim_patients"},{"from":"model.healthcare_analytics.stg_synthea__patients","to":"model.healthcare_analytics.mart_date_state_grid"},{"from":"model.healthcare_analytics.stg_synthea__payers","to":"model.healthcare_analytics.dim_payers"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.fct_cost_analysis"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.fct_patient_summary"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.fct_provider_metrics"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.int_encounters__enriched"},{"from":"model.healthcare_analytics.stg_synthea__providers","to":"model.healthcare_analytics.dim_providers"}]}</script>
+<script type="application/json" id="explore-dag-data">{"nodes":[{"id":"model.healthcare_analytics.dim_conditions","name":"dim_conditions","not_compiled":false},{"id":"model.healthcare_analytics.dim_date","name":"dim_date","not_compiled":false},{"id":"model.healthcare_analytics.dim_organizations","name":"dim_organizations","not_compiled":false},{"id":"model.healthcare_analytics.dim_patients","name":"dim_patients","not_compiled":false},{"id":"model.healthcare_analytics.dim_payers","name":"dim_payers","not_compiled":false},{"id":"model.healthcare_analytics.dim_providers","name":"dim_providers","not_compiled":false},{"id":"model.healthcare_analytics.fct_clinical_events","name":"fct_clinical_events","not_compiled":false},{"id":"model.healthcare_analytics.fct_condition_cohorts","name":"fct_condition_cohorts","not_compiled":false},{"id":"model.healthcare_analytics.fct_cost_analysis","name":"fct_cost_analysis","not_compiled":false},{"id":"model.healthcare_analytics.fct_encounters","name":"fct_encounters","not_compiled":false},{"id":"model.healthcare_analytics.fct_encounters_incremental","name":"fct_encounters_incremental","not_compiled":false},{"id":"model.healthcare_analytics.fct_encounters_monthly","name":"fct_encounters_monthly","not_compiled":false},{"id":"model.healthcare_analytics.fct_encounters_yearly","name":"fct_encounters_yearly","not_compiled":false},{"id":"model.healthcare_analytics.fct_patient_summary","name":"fct_patient_summary","not_compiled":false},{"id":"model.healthcare_analytics.fct_provider_metrics","name":"fct_provider_metrics","not_compiled":false},{"id":"model.healthcare_analytics.int_dq_quarantine__encounters","name":"int_dq_quarantine__encounters","not_compiled":false},{"id":"model.healthcare_analytics.int_dq_quarantine__medications","name":"int_dq_quarantine__medications","not_compiled":false},{"id":"model.healthcare_analytics.int_encounters__enriched","name":"int_encounters__enriched","not_compiled":false},{"id":"model.healthcare_analytics.int_patients__with_conditions","name":"int_patients__with_conditions","not_compiled":false},{"id":"model.healthcare_analytics.mart_date_state_grid","name":"mart_date_state_grid","not_compiled":false},{"id":"model.healthcare_analytics.mart_dq_summary","name":"mart_dq_summary","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__conditions","name":"stg_synthea__conditions","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__encounters","name":"stg_synthea__encounters","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__medications","name":"stg_synthea__medications","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__observations","name":"stg_synthea__observations","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__organizations","name":"stg_synthea__organizations","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__patients","name":"stg_synthea__patients","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__payers","name":"stg_synthea__payers","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__procedures","name":"stg_synthea__procedures","not_compiled":false},{"id":"model.healthcare_analytics.stg_synthea__providers","name":"stg_synthea__providers","not_compiled":false},{"id":"model.healthcare_analytics.v_encounter_summary","name":"v_encounter_summary","not_compiled":false},{"id":"model.healthcare_analytics.v_patient_current_conditions","name":"v_patient_current_conditions","not_compiled":false},{"id":"model.healthcare_analytics.v_provider_active_patients","name":"v_provider_active_patients","not_compiled":false}],"edges":[{"from":"model.healthcare_analytics.dim_conditions","to":"model.healthcare_analytics.fct_condition_cohorts"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_cost_analysis"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_encounters_monthly"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_encounters_yearly"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_patient_summary"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.fct_provider_metrics"},{"from":"model.healthcare_analytics.dim_date","to":"model.healthcare_analytics.mart_date_state_grid"},{"from":"model.healthcare_analytics.dim_organizations","to":"model.healthcare_analytics.dim_providers"},{"from":"model.healthcare_analytics.dim_organizations","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_organizations","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.fct_condition_cohorts"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.int_patients__with_conditions"},{"from":"model.healthcare_analytics.dim_patients","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.dim_payers","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_payers","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.dim_providers","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.dim_providers","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.dim_providers","to":"model.healthcare_analytics.v_provider_active_patients"},{"from":"model.healthcare_analytics.fct_condition_cohorts","to":"model.healthcare_analytics.v_patient_current_conditions"},{"from":"model.healthcare_analytics.fct_condition_cohorts","to":"model.healthcare_analytics.v_provider_active_patients"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_cost_analysis"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_encounters_monthly"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_encounters_yearly"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_patient_summary"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.fct_provider_metrics"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.int_encounters__enriched"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.v_encounter_summary"},{"from":"model.healthcare_analytics.fct_encounters","to":"model.healthcare_analytics.v_provider_active_patients"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.dim_conditions"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.fct_condition_cohorts"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.fct_patient_summary"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.int_encounters__enriched"},{"from":"model.healthcare_analytics.stg_synthea__conditions","to":"model.healthcare_analytics.int_patients__with_conditions"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.fct_encounters"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.fct_encounters_incremental"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.int_dq_quarantine__encounters"},{"from":"model.healthcare_analytics.stg_synthea__encounters","to":"model.healthcare_analytics.mart_dq_summary"},{"from":"model.healthcare_analytics.stg_synthea__medications","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.stg_synthea__medications","to":"model.healthcare_analytics.int_dq_quarantine__medications"},{"from":"model.healthcare_analytics.stg_synthea__medications","to":"model.healthcare_analytics.int_encounters__enriched"},{"from":"model.healthcare_analytics.stg_synthea__medications","to":"model.healthcare_analytics.mart_dq_summary"},{"from":"model.healthcare_analytics.stg_synthea__organizations","to":"model.healthcare_analytics.dim_organizations"},{"from":"model.healthcare_analytics.stg_synthea__patients","to":"model.healthcare_analytics.dim_patients"},{"from":"model.healthcare_analytics.stg_synthea__patients","to":"model.healthcare_analytics.mart_date_state_grid"},{"from":"model.healthcare_analytics.stg_synthea__payers","to":"model.healthcare_analytics.dim_payers"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.fct_clinical_events"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.fct_cost_analysis"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.fct_patient_summary"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.fct_provider_metrics"},{"from":"model.healthcare_analytics.stg_synthea__procedures","to":"model.healthcare_analytics.int_encounters__enriched"},{"from":"model.healthcare_analytics.stg_synthea__providers","to":"model.healthcare_analytics.dim_providers"}],"cte_dags":{"model.healthcare_analytics.dim_conditions":{"nodes":[{"id":"conditions_source","role":"import"},{"id":"condition_aggregates","role":"transform"},{"id":"deduped","role":"transform"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_conditions.sql","role":"final"}],"edges":[{"from":"conditions_source","to":"condition_aggregates","edge_type":"from"},{"from":"condition_aggregates","to":"deduped","edge_type":"from"},{"from":"deduped","to":"sequenced","edge_type":"from"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.dim_date":{"nodes":[{"id":"date_spine","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_date.sql","role":"final"}],"edges":[{"from":"date_spine","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.dim_organizations":{"nodes":[{"id":"source","role":"import"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_organizations.sql","role":"final"}],"edges":[{"from":"source","to":"sequenced","edge_type":"from"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.dim_patients":{"nodes":[{"id":"snapshot_source","role":"import"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_patients.sql","role":"final"}],"edges":[{"from":"snapshot_source","to":"sequenced","edge_type":"from"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.dim_payers":{"nodes":[{"id":"source","role":"import"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_payers.sql","role":"final"}],"edges":[{"from":"source","to":"sequenced","edge_type":"from"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.dim_providers":{"nodes":[{"id":"providers","role":"import"},{"id":"organizations","role":"import"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_providers.sql","role":"final"}],"edges":[{"from":"providers","to":"sequenced","edge_type":"from"},{"from":"organizations","to":"sequenced","edge_type":"left"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_clinical_events":{"nodes":[{"id":"valid_encounters","role":"import"},{"id":"conditions","role":"import"},{"id":"medications","role":"import"},{"id":"procedures","role":"import"},{"id":"all_events","role":"transform"},{"id":"patients","role":"import"},{"id":"dim_date","role":"import"},{"id":"encounters","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_clinical_events.sql","role":"final"}],"edges":[{"from":"conditions","to":"all_events","edge_type":"union_all"},{"from":"medications","to":"all_events","edge_type":"union_all"},{"from":"procedures","to":"all_events","edge_type":"union_all"},{"from":"all_events","to":"final","edge_type":"from"},{"from":"patients","to":"final","edge_type":"left"},{"from":"encounters","to":"final","edge_type":"left"},{"from":"dim_date","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_condition_cohorts":{"nodes":[{"id":"conditions_source","role":"import"},{"id":"patients","role":"import"},{"id":"dim_conditions","role":"import"},{"id":"condition_windows","role":"transform"},{"id":"with_dimensions","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_condition_cohorts.sql","role":"final"}],"edges":[{"from":"conditions_source","to":"condition_windows","edge_type":"from"},{"from":"condition_windows","to":"with_dimensions","edge_type":"from"},{"from":"patients","to":"with_dimensions","edge_type":"left"},{"from":"dim_conditions","to":"with_dimensions","edge_type":"left"},{"from":"with_dimensions","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_cost_analysis":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"procedures","role":"import"},{"id":"encounters_enriched","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_cost_analysis.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_enriched","edge_type":"from"},{"from":"dim_date","to":"encounters_enriched","edge_type":"left"},{"from":"procedures","to":"encounters_enriched","edge_type":"left"},{"from":"encounters_enriched","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_encounters":{"nodes":[{"id":"encounters","role":"import"},{"id":"patients","role":"import"},{"id":"providers","role":"import"},{"id":"organizations","role":"import"},{"id":"payers","role":"import"},{"id":"dim_date","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_encounters.sql","role":"final"}],"edges":[{"from":"encounters","to":"final","edge_type":"from"},{"from":"patients","to":"final","edge_type":"left"},{"from":"providers","to":"final","edge_type":"left"},{"from":"organizations","to":"final","edge_type":"left"},{"from":"payers","to":"final","edge_type":"left"},{"from":"dim_date","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_encounters_incremental":{"nodes":[{"id":"source","role":"import"},{"id":"(final select)","label":"fct_encounters_incremental.sql","role":"final"}],"edges":[{"from":"source","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_encounters_monthly":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"encounters_with_date","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_encounters_monthly.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_with_date","edge_type":"from"},{"from":"dim_date","to":"encounters_with_date","edge_type":"inner"},{"from":"encounters_with_date","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_encounters_yearly":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"encounters_with_date","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_encounters_yearly.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_with_date","edge_type":"from"},{"from":"dim_date","to":"encounters_with_date","edge_type":"inner"},{"from":"encounters_with_date","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_patient_summary":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"procedures","role":"import"},{"id":"conditions","role":"import"},{"id":"encounters_with_year","role":"transform"},{"id":"conditions_per_patient_year","role":"transform"},{"id":"patient_year_agg","role":"transform"},{"id":"with_conditions","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_patient_summary.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_with_year","edge_type":"from"},{"from":"dim_date","to":"encounters_with_year","edge_type":"inner"},{"from":"procedures","to":"encounters_with_year","edge_type":"left"},{"from":"conditions","to":"conditions_per_patient_year","edge_type":"from"},{"from":"encounters_with_year","to":"patient_year_agg","edge_type":"from"},{"from":"patient_year_agg","to":"with_conditions","edge_type":"from"},{"from":"conditions_per_patient_year","to":"with_conditions","edge_type":"left"},{"from":"with_conditions","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.fct_provider_metrics":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"procedures","role":"import"},{"id":"encounters_with_date","role":"transform"},{"id":"provider_month_agg","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_provider_metrics.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_with_date","edge_type":"from"},{"from":"dim_date","to":"encounters_with_date","edge_type":"inner"},{"from":"procedures","to":"encounters_with_date","edge_type":"left"},{"from":"encounters_with_date","to":"provider_month_agg","edge_type":"from"},{"from":"provider_month_agg","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.int_encounters__enriched":{"nodes":[{"id":"encounters","role":"import"},{"id":"conditions","role":"import"},{"id":"medications","role":"import"},{"id":"procedures","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"int_encounters__enriched.sql","role":"final"}],"edges":[{"from":"encounters","to":"final","edge_type":"from"},{"from":"conditions","to":"final","edge_type":"left"},{"from":"medications","to":"final","edge_type":"left"},{"from":"procedures","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.int_patients__with_conditions":{"nodes":[{"id":"patients","role":"import"},{"id":"conditions","role":"import"},{"id":"condition_stats","role":"transform"},{"id":"chronic_flags","role":"transform"},{"id":"chronic_count","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"int_patients__with_conditions.sql","role":"final"}],"edges":[{"from":"conditions","to":"condition_stats","edge_type":"from"},{"from":"conditions","to":"chronic_flags","edge_type":"from"},{"from":"chronic_flags","to":"chronic_count","edge_type":"from"},{"from":"patients","to":"final","edge_type":"from"},{"from":"condition_stats","to":"final","edge_type":"left"},{"from":"chronic_flags","to":"final","edge_type":"left"},{"from":"chronic_count","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.mart_date_state_grid":{"nodes":[{"id":"months","role":"import"},{"id":"states","role":"import"},{"id":"grid","role":"transform"},{"id":"(final select)","label":"mart_date_state_grid.sql","role":"final"}],"edges":[{"from":"months","to":"grid","edge_type":"from"},{"from":"states","to":"grid","edge_type":"cross"},{"from":"grid","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.mart_dq_summary":{"nodes":[{"id":"encounter_metrics","role":"import"},{"id":"medication_metrics","role":"import"},{"id":"combined_metrics","role":"transform"},{"id":"(final select)","label":"mart_dq_summary.sql","role":"final"}],"edges":[{"from":"encounter_metrics","to":"combined_metrics","edge_type":"union_all"},{"from":"medication_metrics","to":"combined_metrics","edge_type":"union_all"},{"from":"combined_metrics","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__conditions":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_surrogate_key","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__conditions.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_surrogate_key","edge_type":"from"},{"from":"with_surrogate_key","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__encounters":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_dq_flags","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__encounters.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_dq_flags","edge_type":"from"},{"from":"with_dq_flags","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__medications":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_row_number","role":"transform"},{"id":"with_surrogate_key","role":"transform"},{"id":"with_dq_flags","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__medications.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_row_number","edge_type":"from"},{"from":"with_row_number","to":"with_surrogate_key","edge_type":"from"},{"from":"with_surrogate_key","to":"with_dq_flags","edge_type":"from"},{"from":"with_dq_flags","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__observations":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_row_number","role":"transform"},{"id":"with_surrogate_key","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__observations.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_row_number","edge_type":"from"},{"from":"with_row_number","to":"with_surrogate_key","edge_type":"from"},{"from":"with_surrogate_key","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__organizations":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__organizations.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__patients":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__patients.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__payers":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__payers.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__procedures":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_surrogate_key","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__procedures.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_surrogate_key","edge_type":"from"},{"from":"with_surrogate_key","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.stg_synthea__providers":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__providers.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.v_encounter_summary":{"nodes":[{"id":"encounters","role":"import"},{"id":"patients","role":"import"},{"id":"providers","role":"import"},{"id":"organizations","role":"import"},{"id":"payers","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"v_encounter_summary.sql","role":"final"}],"edges":[{"from":"encounters","to":"final","edge_type":"from"},{"from":"patients","to":"final","edge_type":"left"},{"from":"providers","to":"final","edge_type":"left"},{"from":"organizations","to":"final","edge_type":"left"},{"from":"payers","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.v_patient_current_conditions":{"nodes":[{"id":"condition_cohorts","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"v_patient_current_conditions.sql","role":"final"}],"edges":[{"from":"condition_cohorts","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"model.healthcare_analytics.v_provider_active_patients":{"nodes":[{"id":"providers","role":"import"},{"id":"current_conditions","role":"import"},{"id":"patient_recent_encounters","role":"import"},{"id":"patient_provider_assignment","role":"transform"},{"id":"active_conditions_by_provider","role":"transform"},{"id":"provider_summary","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"v_provider_active_patients.sql","role":"final"}],"edges":[{"from":"patient_recent_encounters","to":"patient_provider_assignment","edge_type":"from"},{"from":"current_conditions","to":"active_conditions_by_provider","edge_type":"from"},{"from":"patient_provider_assignment","to":"active_conditions_by_provider","edge_type":"inner"},{"from":"active_conditions_by_provider","to":"provider_summary","edge_type":"from"},{"from":"providers","to":"final","edge_type":"from"},{"from":"provider_summary","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]}}}</script>
 
 <script>
 
@@ -500,9 +536,20 @@ <h1>Model lineage</h1>
   // ---- HIGHLIGHT (click / search-select; in-place, never a commit) --------
   var highlighted = null;
 
+  // cute-dbt#102 — page-local highlight observer hook: the CTE-view
+  // engine (explore-cte.js) gates + retargets its view off this event.
+  // It is NOT the external-drive signal: data-selected-model stays
+  // Space-commit-only (the one write site below).
+  function notifyHighlight(id) {
+    document.dispatchEvent(
+      new CustomEvent("cute-explore-highlight", { detail: { id: id } })
+    );
+  }
+
   function clearHighlight() {
     cy.elements().removeClass("dim sel trace");
     highlighted = null;
+    notifyHighlight(null);
   }
 
   function highlightNode(node) {
@@ -514,6 +561,7 @@ <h1>Model lineage</h1>
       node.removeClass("dim").addClass("sel");
     });
     highlighted = node;
+    notifyHighlight(node.id());
   }
 
   // ---- FOCUS COMMIT (Space only — the one selectedModel write site) -------
@@ -668,6 +716,284 @@ <h1>Model lineage</h1>
 })();
 /* end of cute-dbt explore lineage engine v1 (cute-dbt#101) */
 
+</script>
+<script>
+
+/* cute-dbt explore CTE engine v1 (cute-dbt#102)
+   ----------------------------------------------------------------------------
+   The CTE <-> model view toggle on explore's dag.html plus the per-model
+   Cytoscape CTE DAG it renders. Binding decision (epic cute-dbt#99 V3):
+   the CTE view follows the HIGHLIGHTED model — the same in-page selection
+   the click / fuzzy-search-select affordance drives (a Space focus commit
+   implies a highlight, so a committed model is always viewable). With no
+   highlight the CTE arm is disabled; while the CTE view is active a
+   search-select retargets it in place, and a cleared highlight falls back
+   to the lineage view.
+
+   View-state contract (the cute-dbt#102 AC): switching views is LOCAL
+   STATE on the same page — no reload, and the lineage Cytoscape instance
+   is NEVER rebuilt (its pan / zoom / highlight survive a round trip; only
+   cy.resize() runs after un-hiding). The CTE instance rebuilds only on a
+   model retarget — a view change, the cyto-dag.js model-switch precedent;
+   per-interaction work inside a built instance stays in-place.
+
+   Data: the `explore-dag-data` carrier's `cte_dags` map (full model node
+   id -> the SAME DagPayload the report renders for that model:
+   role-classified nodes + join-typed edges, parsed once in Rust). A
+   missing entry on a `not_compiled` model renders the labeled fail-open
+   degraded view (never an error); missing on a compiled model renders
+   the "no CTE structure" sparse state.
+
+   Init hygiene (the ADR-4-amendment contract, explore-page variant):
+   - node labels are CANVAS TEXT — XSS-safe by construction; hostile
+     manifest-derived names draw as glyphs, never parse as HTML.
+   - explicit non-webfont system fontFamily (zero-egress: no font fetch).
+   - the dagre layout runs IN-THREAD via the vendored cytoscape-dagre UMD
+     already registered for the lineage view (never the EPL
+     cytoscape-elk) and NO workers.
+   - measured node widths via canvas measureText (no deprecated
+     `width: label`, no custom wheelSensitivity — both emit console
+     warnings the headless gate rejects).
+   - handlers are bound from THIS file; DOM strings land via textContent
+     only; this file never writes data-selected-model (the Space commit
+     in explore-lineage.js stays the single write site).
+
+   First-party, NOT vendored: lives at templates/explore-cte.js, embedded
+   at compile time via asset_embed::EXPLORE_CTE_JS (include_str!) and
+   interpolated inline by the askama renderer. Banner-pin +
+   end-of-file-sentinel tests in src/adapters/asset_embed.rs guard the
+   include. */
+(function () {
+  "use strict";
+
+  var carrier = document.getElementById("explore-dag-data");
+  if (!carrier) return;
+  var data = JSON.parse(carrier.textContent);
+  if (!data.nodes || !data.nodes.length) return; // empty manifest: no views
+  var cteDags = data.cte_dags || {};
+
+  var toggle = document.querySelector(".view-toggle");
+  var lineageView = document.querySelector(".lineage-view");
+  var cteView = document.querySelector(".cte-view");
+  if (!toggle || !lineageView || !cteView) return;
+  var btnLineage = toggle.querySelector('[data-view="lineage"]');
+  var btnCte = toggle.querySelector('[data-view="cte"]');
+  var host = cteView.querySelector(".cte-canvas");
+  var titleModel = cteView.querySelector(".cte-view-model");
+  var degraded = cteView.querySelector(".cte-degraded");
+  var sparse = cteView.querySelector(".cte-view-empty");
+
+  // id -> lineage node (bare name + the fail-open not_compiled flag).
+  // Prototype-less so a hostile model id can never collide with a
+  // built-in prototype property (the cyto-dag.js precedent).
+  var modelById = Object.create(null);
+  data.nodes.forEach(function (n) { modelById[n.id] = n; });
+
+  var view = "lineage";
+  var highlightedId = null;
+  var cy = null;                // the CTE instance (rebuilt per retarget)
+  var renderedModelId = null;
+
+  // ---- style (canvas text, measured widths, role + join vocabulary) ------
+  var FONT_STACK = 'ui-monospace, SFMono-Regular, Menlo, Consolas, monospace';
+  var measureCtx = document.createElement("canvas").getContext("2d");
+  measureCtx.font = "13px " + FONT_STACK;
+  function labelWidth(label) {
+    return Math.min(300, Math.ceil(measureCtx.measureText(label).width) + 26);
+  }
+
+  // The join-type edge label: the DagPayload wire key with underscores
+  // opened up (`union_all` -> `union all`).
+  function joinLabel(etype) {
+    return String(etype || "from").replace(/_/g, " ");
+  }
+
+  // Explore-page light palette, role vocabulary aligned with the report
+  // (final / import / transform) and the lineage view's hues.
+  var ROLES = {
+    final: { fill: "#e8f1f8", stroke: "#0072B2", shape: "hexagon" },
+    import: { fill: "#eef7ee", stroke: "#1f8a5b", shape: "round-rectangle" },
+    transform: { fill: "#f4f4f5", stroke: "#6b6b76", shape: "rectangle" }
+  };
+
+  function roleStyle(role) {
+    var r = ROLES[role] || ROLES.transform;
+    return {
+      "background-color": r.fill,
+      "border-color": r.stroke,
+      "shape": r.shape
+    };
+  }
+
+  function styleSheet() {
+    return [
+      { selector: "node", style: {
+        "label": "data(label)",
+        "text-valign": "center",
+        "text-halign": "center",
+        "font-family": FONT_STACK,
+        "font-size": 13,
+        "color": "#1c1c1f",
+        "text-wrap": "ellipsis",
+        "text-max-width": 280,
+        "width": "data(w)",
+        "height": 30,
+        "border-width": 1.6,
+        "background-color": ROLES.transform.fill,
+        "border-color": ROLES.transform.stroke,
+        "shape": "rectangle"
+      }},
+      { selector: 'node[role = "import"]', style: roleStyle("import") },
+      { selector: 'node[role = "final"]', style: roleStyle("final") },
+      { selector: "edge", style: {
+        "curve-style": "bezier",
+        "width": 1.8,
+        "line-color": "#8b8b96",
+        "target-arrow-shape": "triangle",
+        "target-arrow-color": "#8b8b96",
+        "arrow-scale": 1.1,
+        "label": "data(elabel)",
+        "font-family": FONT_STACK,
+        "font-size": 10,
+        "color": "#555",
+        "text-rotation": "autorotate",
+        "text-background-color": "#fcfcfd",
+        "text-background-opacity": 1,
+        "text-background-padding": "2px"
+      }},
+      { selector: 'edge[etype = "union_all"], edge[etype = "union_distinct"]', style: {
+        "line-style": "dashed",
+        "line-dash-pattern": [6, 3]
+      }}
+    ];
+  }
+
+  // ---- elements off one cte_dags DagPayload entry --------------------------
+  function buildElements(dag) {
+    var els = [];
+    dag.nodes.forEach(function (n) {
+      var label = String(n.label || n.id);
+      els.push({
+        group: "nodes",
+        // Resolved only via cy.getElementById — a selector-hostile CTE
+        // alias is inert (the cute-dbt#155 / #180 precedent).
+        data: {
+          id: n.id,
+          label: label,
+          w: labelWidth(label),
+          role: n.role || "transform"
+        }
+      });
+    });
+    (dag.edges || []).forEach(function (e, i) {
+      els.push({
+        group: "edges",
+        data: {
+          id: "e" + i,
+          source: e.from,
+          target: e.to,
+          etype: e.edge_type || "from",
+          elabel: joinLabel(e.edge_type)
+        }
+      });
+    });
+    return els;
+  }
+
+  // ---- CTE render (per-model; a view change, so a rebuild is allowed) -----
+  function destroyCte() {
+    if (cy) { cy.destroy(); cy = null; }
+  }
+
+  function renderCte(modelId) {
+    renderedModelId = modelId;
+    var m = modelById[modelId];
+    titleModel.textContent = m ? m.name : String(modelId);
+    host.hidden = false;
+    degraded.hidden = true;
+    sparse.hidden = true;
+    destroyCte();
+    var dag = Object.prototype.hasOwnProperty.call(cteDags, modelId)
+      ? cteDags[modelId]
+      : null;
+    if (!dag) {
+      host.hidden = true;
+      if (m && m.not_compiled) {
+        // Fail-open: the labeled degraded view, never an error.
+        degraded.textContent = m.name + " has no compiled SQL in this manifest"
+          + " (dbt parse) — run dbt compile to fill in its CTE DAG."
+          + " The model still renders in the lineage view.";
+        degraded.hidden = false;
+      } else {
+        sparse.hidden = false;
+      }
+      return;
+    }
+    cy = window.cytoscape({
+      container: host,
+      elements: buildElements(dag),
+      style: styleSheet(),
+      // Same vendored dagre left-to-right ranks as the lineage view —
+      // the one registered layout extension on this page.
+      layout: { name: "dagre", rankDir: "LR", nodeSep: 18, rankSep: 90, edgeSep: 12, fit: true, padding: 24 },
+      minZoom: 0.2,
+      maxZoom: 2.5,
+      boxSelectionEnabled: false
+    });
+  }
+
+  // ---- the view toggle (chrome + selection persist; same page) ------------
+  function setView(next) {
+    if (next === view) return;
+    if (next === "cte" && !highlightedId) return; // gated on a highlight
+    view = next;
+    var isCte = view === "cte";
+    lineageView.hidden = isCte;
+    cteView.hidden = !isCte;
+    btnLineage.classList.toggle("is-active", !isCte);
+    btnLineage.setAttribute("aria-pressed", String(!isCte));
+    btnCte.classList.toggle("is-active", isCte);
+    btnCte.setAttribute("aria-pressed", String(isCte));
+    if (isCte) {
+      if (renderedModelId !== highlightedId) {
+        renderCte(highlightedId);
+      } else if (cy) {
+        cy.resize(); // dimensions only — pan/zoom persist
+      }
+    } else if (window.CuteExploreLineage) {
+      // The lineage instance was never rebuilt: its pan/zoom/highlight
+      // persist; only the canvas dimensions need a refresh.
+      var lcy = window.CuteExploreLineage.cyInstance();
+      if (lcy) lcy.resize();
+    }
+  }
+
+  // The lineage engine's page-local highlight event gates the CTE arm
+  // and retargets an active CTE view in place.
+  document.addEventListener("cute-explore-highlight", function (ev) {
+    highlightedId = ev.detail ? ev.detail.id : null;
+    btnCte.disabled = !highlightedId;
+    if (view !== "cte") return;
+    if (!highlightedId) {
+      setView("lineage");
+      return;
+    }
+    if (highlightedId !== renderedModelId) renderCte(highlightedId);
+  });
+
+  btnLineage.addEventListener("click", function () { setView("lineage"); });
+  btnCte.addEventListener("click", function () { setView("cte"); });
+
+  // Public seam: the headless suites drive + observe the toggle through
+  // this (the window.CuteExploreLineage precedent).
+  window.CuteExploreCte = {
+    activeView: function () { return view; },
+    cyInstance: function () { return cy; },
+    renderedModelId: function () { return renderedModelId; }
+  };
+})();
+/* end of cute-dbt explore CTE engine v1 (cute-dbt#102) */
+
 </script>
 </body>
 </html>
\ No newline at end of file
diff --git a/examples/explore/tests.html b/examples/explore/tests.html
index 2d1e5572..08bf4a63 100644
--- a/examples/explore/tests.html
+++ b/examples/explore/tests.html
@@ -246,11 +246,39 @@
 .model-path { color: #555; font-size: 0.85rem; margin: 0 0 0.4rem; }
 .not-compiled-badge { font-size: 0.7em; vertical-align: middle; padding: 0.1rem 0.45rem; border: 1.5px dashed #b07400; border-radius: 4px; background: #f4f4f5; color: #1c1c1f; }
 .explore-tests { margin-bottom: 0.5rem; }
-.explore-test .test-name { font-weight: 600; }
 .explore-test .test-shape { color: #555; font-size: 0.85rem; }
 .explore-test .test-description { color: #555; font-size: 0.9rem; margin: 0.1rem 0 0; }
 .no-tests { color: #555; font-style: italic; }
 .explore-empty { color: #555; font-style: italic; }
+/* cute-dbt#102 — explore-local styling for the SHARED test-card partial
+   (report.html styles the same markup through its chassis CSS, which
+   this light page deliberately does not embed). */
+.explore-viewer { border-top: 1px solid #ddd; padding-top: 0.75rem; margin-top: 0.75rem; }
+.explore-viewer > h2 { margin-bottom: 0.4rem; }
+.test-card { border: 1px solid #c5c5cc; border-radius: 6px; padding: 0.75rem 1rem; background: #fcfcfd; }
+.test-card-head { display: flex; align-items: baseline; gap: 1rem; flex-wrap: wrap; }
+.test-select-field label { font-weight: 600; margin-right: 0.4rem; }
+/* Explore is full-manifest by design: there is no updated/context split,
+   so the partial's scope toggle is inert chrome here — hidden, not
+   forked out of the shared markup. */
+.test-mode-toggle { display: none; }
+.test-badges .tag-badge { display: inline-block; font-size: 0.75rem; color: #1c1c1f; border: 1px solid #c5c5cc; border-radius: 4px; padding: 0 0.35rem; background: #f4f4f5; margin-right: 0.25rem; }
+.test-description { color: #333; margin: 0.5rem 0 0; }
+.test-defined-in { color: #555; font-size: 0.85rem; margin: 0.3rem 0 0; }
+.panel-row { display: flex; gap: 1rem; flex-wrap: wrap; margin-top: 0.75rem; }
+.panel { flex: 1 1 22rem; min-width: 0; border: 1px solid #c5c5cc; border-radius: 6px; padding: 0.6rem 0.8rem; background: #fcfcfd; }
+.panel-header { display: flex; align-items: baseline; gap: 0.6rem; }
+.panel-header h2 { font-size: 1.1rem; margin: 0 0 0.4rem; }
+.table-header { display: flex; align-items: baseline; gap: 0.6rem; flex-wrap: wrap; }
+.table-title { margin: 0.4rem 0 0.2rem; font-size: 0.95rem; }
+.row-count-badge, .format-badge, .this-badge { font-size: 0.75rem; color: #555; border: 1px solid #c5c5cc; border-radius: 4px; padding: 0 0.35rem; background: #f4f4f5; }
+.fixture-provenance { font-size: 0.8rem; color: #555; }
+table.given-table, table.expected-table { font-size: 0.85rem; margin: 0.3rem 0 0.6rem; }
+.cell-null { color: #888; font-style: italic; }
+.empty-hint, .given-empty { color: #555; font-style: italic; }
+.sql-block { font-size: 0.85rem; }
+.test-jump { background: none; border: none; padding: 0; color: #1d7484; font: inherit; font-weight: 600; cursor: pointer; text-decoration: underline; }
+.test-jump:hover, .test-jump:focus { color: #144f5a; }
 </style>
 </head>
 <body>
@@ -267,6 +295,47 @@ <h1>Unit tests</h1>
 
 
 
+<section class="explore-viewer" aria-label="Unit-test viewer">
+<h2>Unit-test viewer</h2>
+<section class="test-section" aria-label="Unit test">
+  <div class="test-card">
+    <div class="test-card-head">
+      <div class="selector-field test-select-field">
+        <label for="test-select">Unit test</label>
+        <select id="test-select"></select>
+      </div>
+      <div class="test-mode-toggle" role="group" aria-label="Test scope" data-testid="updated-toggle">
+        <button type="button" data-test-mode="updated" class="is-active" aria-pressed="true">Updated only</button>
+        <button type="button" data-test-mode="all" aria-pressed="false">All tests</button>
+      </div>
+      <div class="test-badges"></div>
+    </div>
+    <p class="test-description" hidden></p>
+    <div class="test-details-body"></div>
+  </div>
+</section>
+
+<div class="panel-row">
+
+  <section class="panel left-panel" aria-label="Given inputs">
+    
+    <div class="panel-header">
+      <h2>Given</h2>
+    </div>
+    <div class="left-panel-body" data-mode="inputs"></div>
+  </section>
+
+  <section class="panel expected-panel" aria-label="Expected output">
+    <div class="panel-header">
+      <h2>Expected</h2>
+      <span class="row-count-badge expected-rowcount">0 rows</span>
+    </div>
+    <div class="expected-body"></div>
+  </section>
+
+</div>
+</section>
+
 <section class="explore-model" data-model-id="model.healthcare_analytics.dim_conditions" aria-label="Model dim_conditions">
   <h2>dim_conditions</h2>
   <p class="model-path"><code>models/marts/analytics/dim_conditions.sql</code></p>
@@ -299,8 +368,9 @@ <h2>dim_patients</h2>
   <h2>dim_payers</h2>
   <p class="model-path"><code>models/marts/core/dim_payers.sql</code></p>
   <ul class="explore-tests">
-    <li class="explore-test">
-      <span class="test-name">test_dim_payers_injects_unknown_sentinel</span>
+    <li class="explore-test" data-test-id="unit_test.healthcare_analytics.dim_payers.test_dim_payers_injects_unknown_sentinel">
+      
+      <button type="button" class="test-jump" data-test-id="unit_test.healthcare_analytics.dim_payers.test_dim_payers_injects_unknown_sentinel">test_dim_payers_injects_unknown_sentinel</button>
       <span class="test-shape">&mdash; 1 given, expects 2 rows</span>
       <p class="test-description">dim_payers UNION-ALLs an unknown-member sentinel row (payer_key = -1)
 with the sequenced source rows. This test verifies the sentinel
@@ -356,8 +426,9 @@ <h2>fct_encounters</h2>
   <h2>fct_encounters_incremental</h2>
   <p class="model-path"><code>models/marts/core/fct_encounters_incremental.sql</code></p>
   <ul class="explore-tests">
-    <li class="explore-test">
-      <span class="test-name">test_fct_encounters_incremental_appends_new_encounters</span>
+    <li class="explore-test" data-test-id="unit_test.healthcare_analytics.fct_encounters_incremental.test_fct_encounters_incremental_appends_new_encounters">
+      
+      <button type="button" class="test-jump" data-test-id="unit_test.healthcare_analytics.fct_encounters_incremental.test_fct_encounters_incremental_appends_new_encounters">test_fct_encounters_incremental_appends_new_encounters</button>
       <span class="test-shape">&mdash; 2 givens, expects 1 row</span>
       <p class="test-description">fct_encounters_incremental appends encounters newer than the latest loaded start_time. With is_incremental() true only the new encounter is merged; Expected is that single inserted row (the materialization delta), not the resulting table.</p>
       
@@ -427,8 +498,9 @@ <h2>int_patients__with_conditions</h2>
   <h2>mart_date_state_grid</h2>
   <p class="model-path"><code>models/marts/analytics/mart_date_state_grid.sql</code></p>
   <ul class="explore-tests">
-    <li class="explore-test">
-      <span class="test-name">test_mart_date_state_grid_cross_joins_months_and_states</span>
+    <li class="explore-test" data-test-id="unit_test.healthcare_analytics.mart_date_state_grid.test_mart_date_state_grid_cross_joins_months_and_states">
+      
+      <button type="button" class="test-jump" data-test-id="unit_test.healthcare_analytics.mart_date_state_grid.test_mart_date_state_grid_cross_joins_months_and_states">test_mart_date_state_grid_cross_joins_months_and_states</button>
       <span class="test-shape">&mdash; 2 givens, expects 4 rows</span>
       <p class="test-description">mart_date_state_grid CROSS JOINs the distinct calendar months from
 dim_date with the distinct non-null patient states from staging.
@@ -449,8 +521,9 @@ <h2>mart_date_state_grid</h2>
   <h2>mart_dq_summary</h2>
   <p class="model-path"><code>models/marts/analytics/mart_dq_summary.sql</code></p>
   <ul class="explore-tests">
-    <li class="explore-test">
-      <span class="test-name">test_mart_dq_summary_combines_encounter_and_medication_metrics</span>
+    <li class="explore-test" data-test-id="unit_test.healthcare_analytics.mart_dq_summary.test_mart_dq_summary_combines_encounter_and_medication_metrics">
+      
+      <button type="button" class="test-jump" data-test-id="unit_test.healthcare_analytics.mart_dq_summary.test_mart_dq_summary_combines_encounter_and_medication_metrics">test_mart_dq_summary_combines_encounter_and_medication_metrics</button>
       <span class="test-shape">&mdash; 2 givens, expects 2 rows</span>
       <p class="test-description">mart_dq_summary UNION-ALLs metrics from stg_synthea__encounters
 and stg_synthea__medications. This test mocks two encounter rows
@@ -461,8 +534,9 @@ <h2>mart_dq_summary</h2>
 </p>
       
     </li>
-    <li class="explore-test">
-      <span class="test-name">test_mart_dq_summary_zero_quarantined_when_all_valid</span>
+    <li class="explore-test" data-test-id="unit_test.healthcare_analytics.mart_dq_summary.test_mart_dq_summary_zero_quarantined_when_all_valid">
+      
+      <button type="button" class="test-jump" data-test-id="unit_test.healthcare_analytics.mart_dq_summary.test_mart_dq_summary_zero_quarantined_when_all_valid">test_mart_dq_summary_zero_quarantined_when_all_valid</button>
       <span class="test-shape">&mdash; 2 givens, expects 2 rows</span>
       <p class="test-description">mart_dq_summary should report zero quarantined_count and 0.00
 quarantine_rate_pct when every upstream row passes data-quality
@@ -517,8 +591,9 @@ <h2>stg_synthea__organizations</h2>
   <h2>stg_synthea__patients</h2>
   <p class="model-path"><code>models/staging/synthea/stg_synthea__patients.sql</code></p>
   <ul class="explore-tests">
-    <li class="explore-test">
-      <span class="test-name">test_stg_synthea__patients_renames_and_hashes_source_columns</span>
+    <li class="explore-test" data-test-id="unit_test.healthcare_analytics.stg_synthea__patients.test_stg_synthea__patients_renames_and_hashes_source_columns">
+      
+      <button type="button" class="test-jump" data-test-id="unit_test.healthcare_analytics.stg_synthea__patients.test_stg_synthea__patients_renames_and_hashes_source_columns">test_stg_synthea__patients_renames_and_hashes_source_columns</button>
       <span class="test-shape">&mdash; 1 given, expects 1 row</span>
       <p class="test-description">stg_synthea__patients renames the raw Synthea UPPERCASE columns to
 snake_case and hashes the SSN with md5. The given mocks the
@@ -580,5 +655,276 @@ <h2>v_provider_active_patients</h2>
 
 
 <script type="application/json" id="cute-dbt-data">{"baseline":"","models":[{"name":"dim_conditions","path":"models/marts/analytics/dim_conditions.sql","description":"Master condition dimension for healthcare analytics.\nOne row per unique ICD/SNOMED condition code, deduplicated from staging.\nUse for filtering and grouping by condition across fact tables.\n\nUse cases:\n- Condition-based cohort analysis\n- Disease prevalence tracking\n- Condition frequency and distribution reporting\n- Join target for condition-related facts\n","dag":{"nodes":[{"id":"conditions_source","role":"import"},{"id":"condition_aggregates","role":"transform"},{"id":"deduped","role":"transform"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_conditions.sql","role":"final"}],"edges":[{"from":"conditions_source","to":"condition_aggregates","edge_type":"from"},{"from":"condition_aggregates","to":"deduped","edge_type":"from"},{"from":"deduped","to":"sequenced","edge_type":"from"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","condition_aggregates":"condition_aggregates as (\n    select\n        condition_code\n        , condition_description\n        , min(condition_start_date) as first_occurrence_date\n        , max(coalesce(condition_end_date, condition_start_date)) as last_occurrence_date\n        , count(distinct patient_id) as patient_count\n        , count(distinct encounter_id) as encounter_count\n    from conditions_source\n    group by condition_code, condition_description\n)","conditions_source":"conditions_source as (\n    select\n        -- cast to varchar for consistent handling (source is BIGINT SNOMED codes)\n        cast(condition_code as varchar) as condition_code\n        , condition_description\n        , patient_id\n        , encounter_id\n        , condition_start_date\n        , condition_end_date\n    from \"memory\".\"main_staging\".\"stg_synthea__conditions\"\n    where condition_code is not null\n)","deduped":"deduped as (\n    select\n        condition_code\n        , condition_description\n        , first_occurrence_date\n        , last_occurrence_date\n        , patient_count\n        , encounter_count\n        , row_number() over (\n            partition by condition_code\n            order by encounter_count desc, condition_description asc\n        ) as rn\n    from condition_aggregates\n)","final":"final as (\n    select\n        condition_key\n        , condition_code\n        , condition_description\n        , first_occurrence_date\n        , last_occurrence_date\n        , patient_count\n        , encounter_count\n        , current_timestamp as _loaded_at\n    from unknown_member\n\n    union all\n\n    select\n        condition_key\n        , condition_code\n        , condition_description\n        , first_occurrence_date\n        , last_occurrence_date\n        , patient_count\n        , encounter_count\n        , current_timestamp as _loaded_at\n    from sequenced\n)","sequenced":"sequenced as (\n    select\n        -- surrogate key (starting from 1, reserving -1 for unknown)\n        row_number() over (order by condition_code) as condition_key\n\n        -- natural key\n        , condition_code\n\n        -- attributes\n        , condition_description\n        , first_occurrence_date\n        , last_occurrence_date\n\n        -- metrics\n        , patient_count\n        , encounter_count\n\n    from deduped\n    where rn = 1\n)","unknown_member":"unknown_member as (\n    select\n        -1 as condition_key\n        , 'UNKNOWN' as condition_code\n        , 'Unknown Condition' as condition_description\n        , cast(null as date) as first_occurrence_date\n        , cast(null as date) as last_occurrence_date\n        , 0 as patient_count\n        , 0 as encounter_count\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='condition_key',\n        tags=['analytics', 'marts', 'dimension']\n    )\n}}\n\n{#\n    Condition Master Dimension\n\n    Sources: ICD/SNOMED condition codes from Synthea\n    Grain: One row per unique condition code\n    Primary use: Filtering encounters/observations by condition, disease management analysis\n\n    Deduplication: Aggregates from stg_synthea__conditions to get one row per code\n    with summary statistics (patient count, encounter count, date ranges).\n#}\n\nwith conditions_source as (\n    select\n        -- cast to varchar for consistent handling (source is BIGINT SNOMED codes)\n        cast(condition_code as varchar) as condition_code\n        , condition_description\n        , patient_id\n        , encounter_id\n        , condition_start_date\n        , condition_end_date\n    from {{ ref('stg_synthea__conditions') }}\n    where condition_code is not null\n),\n\ncondition_aggregates as (\n    select\n        condition_code\n        , condition_description\n        , min(condition_start_date) as first_occurrence_date\n        , max(coalesce(condition_end_date, condition_start_date)) as last_occurrence_date\n        , count(distinct patient_id) as patient_count\n        , count(distinct encounter_id) as encounter_count\n    from conditions_source\n    group by condition_code, condition_description\n),\n\n-- deduplicate in case same code has different descriptions\ndeduped as (\n    select\n        condition_code\n        , condition_description\n        , first_occurrence_date\n        , last_occurrence_date\n        , patient_count\n        , encounter_count\n        , row_number() over (\n            partition by condition_code\n            order by encounter_count desc, condition_description asc\n        ) as rn\n    from condition_aggregates\n),\n\nsequenced as (\n    select\n        -- surrogate key (starting from 1, reserving -1 for unknown)\n        row_number() over (order by condition_code) as condition_key\n\n        -- natural key\n        , condition_code\n\n        -- attributes\n        , condition_description\n        , first_occurrence_date\n        , last_occurrence_date\n\n        -- metrics\n        , patient_count\n        , encounter_count\n\n    from deduped\n    where rn = 1\n),\n\n-- unknown member for handling missing dimension lookups\nunknown_member as (\n    select\n        -1 as condition_key\n        , 'UNKNOWN' as condition_code\n        , 'Unknown Condition' as condition_description\n        , cast(null as date) as first_occurrence_date\n        , cast(null as date) as last_occurrence_date\n        , 0 as patient_count\n        , 0 as encounter_count\n),\n\nfinal as (\n    select\n        condition_key\n        , condition_code\n        , condition_description\n        , first_occurrence_date\n        , last_occurrence_date\n        , patient_count\n        , encounter_count\n        , current_timestamp as _loaded_at\n    from unknown_member\n\n    union all\n\n    select\n        condition_key\n        , condition_code\n        , condition_description\n        , first_occurrence_date\n        , last_occurrence_date\n        , patient_count\n        , encounter_count\n        , current_timestamp as _loaded_at\n    from sequenced\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.dim_conditions","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_dim_conditions_condition_key.93802fac5a"]},"evidence":[{"label":"unique_key","value":"condition_key"}],"pin_node":"(final select)"},{"check":"union.arm-coverage","tier":"high","instrument":"unit-test","model_id":"model.healthcare_analytics.dim_conditions","construct":"union[final]","verdict":{"status":"uncovered"},"evidence":[{"label":"union","value":"final (2 arms: sequenced, unknown_member)"},{"label":"unexercised arm","value":"sequenced — no given row reaches ref('stg_synthea__conditions')"},{"label":"unattributable arm","value":"unknown_member — no resolvable upstream relation"}],"recommendation":"Add (or fill) a given row for each unexercised UNION arm's input so every arm contributes at least one row, then extend `expect` with the row(s) that arm should emit. This finding's evidence carries the per-arm input and a given-row sketch.","pin_node":"final","sketches":["- input: ref('stg_synthea__conditions')\n  rows:\n    - {_loaded_at: ..., condition_code: ..., condition_description: ..., condition_end_date: ..., condition_id: ..., condition_start_date: ..., encounter_id: ..., patient_id: ...}"]}]},{"name":"dim_date","path":"models/marts/core/dim_date.sql","description":"Calendar dimension covering 1909-01-01 to 2025-12-31. Provides date attributes, day/week/month/quarter/year hierarchies, weekend flags, and US holiday identification.\n","dag":{"nodes":[{"id":"date_spine","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_date.sql","role":"final"}],"edges":[{"from":"date_spine","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","date_spine":"date_spine as (\n    \n    \n    with\n        base_dates as (\n    with\n        date_spine as (\n\n            \n\n    \n    with\n        rawdata as (\n\n            \n\n    \n\n    with\n        p as (\n            select 0 as generated_number\n            union all\n            select 1\n        ),\n        unioned as (\n\n            select\n\n                \n                    p0.generated_number * power(2, 0)\n                     + \n                \n                    p1.generated_number * power(2, 1)\n                     + \n                \n                    p2.generated_number * power(2, 2)\n                     + \n                \n                    p3.generated_number * power(2, 3)\n                     + \n                \n                    p4.generated_number * power(2, 4)\n                     + \n                \n                    p5.generated_number * power(2, 5)\n                     + \n                \n                    p6.generated_number * power(2, 6)\n                     + \n                \n                    p7.generated_number * power(2, 7)\n                     + \n                \n                    p8.generated_number * power(2, 8)\n                     + \n                \n                    p9.generated_number * power(2, 9)\n                     + \n                \n                    p10.generated_number * power(2, 10)\n                     + \n                \n                    p11.generated_number * power(2, 11)\n                     + \n                \n                    p12.generated_number * power(2, 12)\n                     + \n                \n                    p13.generated_number * power(2, 13)\n                     + \n                \n                    p14.generated_number * power(2, 14)\n                     + \n                \n                    p15.generated_number * power(2, 15)\n                    \n                \n                + 1 as generated_number\n\n            from\n\n            \n                    p as p0  cross join \n            \n                    p as p1  cross join \n            \n                    p as p2  cross join \n            \n                    p as p3  cross join \n            \n                    p as p4  cross join \n            \n                    p as p5  cross join \n            \n                    p as p6  cross join \n            \n                    p as p7  cross join \n            \n                    p as p8  cross join \n            \n                    p as p9  cross join \n            \n                    p as p10  cross join \n            \n                    p as p11  cross join \n            \n                    p as p12  cross join \n            \n                    p as p13  cross join \n            \n                    p as p14  cross join \n            \n                    p as p15 \n            \n\n        )\n\n    select *\n    from unioned\n    where generated_number <= 42733\n    order by generated_number\n\n\n\n        ),\n\n        all_periods as (\n\n            select\n                (\n                    \n\n    (cast('1909-01-01' as timestamp) + cast((row_number() over (order by 1) - 1) as bigint) * interval 1 day)\n                ) as date_day\n            from rawdata\n\n        ),\n\n        filtered as (\n\n            select * from all_periods where date_day <= cast('2025-12-31' as timestamp)\n\n        )\n\n    select *\n    from filtered\n\n\n\n        )\n    select\n        cast(d.date_day as timestamp) as date_day\n    from date_spine d\n\n),\n        dates_with_prior_year_dates as (\n\n            select\n                cast(d.date_day as date) as date_day,\n                cast(\n                    \n\n    (d.date_day + cast(-1 as bigint) * interval 1 year) as date\n                ) as prior_year_date_day,\n                cast(\n                    \n\n    (d.date_day + cast(-364 as bigint) * interval 1 day) as date\n                ) as prior_year_over_year_date_day\n            from base_dates d\n\n        )\n    select\n        d.date_day,\n        cast(\n\n    (d.date_day + cast(-1 as bigint) * interval 1 day) as date) as prior_date_day,\n        cast(\n\n    (d.date_day + cast(1 as bigint) * interval 1 day) as date) as next_date_day,\n        d.prior_year_date_day as prior_year_date_day,\n        d.prior_year_over_year_date_day,\n        -- Sunday(1) to Saturday (7)\n        cast(date_part('dow', d.date_day) + 1 as integer) as day_of_week,\n        -- Monday(1) to Sunday (7)\n        cast(date_part('isodow', d.date_day) as integer) as day_of_week_iso,\n        dayname(d.date_day) as day_of_week_name,\n        substr(dayname(d.date_day), 1, 3) as day_of_week_name_short,\n        date_part('day', d.date_day) as day_of_month,\n        date_part('dayofyear', d.date_day) as day_of_year,\n\n        -- Sunday as week start date\n    cast(\n        \n\n    (date_trunc('week', \n\n    (d.date_day + cast(1 as bigint) * interval 1 day)) + cast(-1 as bigint) * interval 1 day) as date\n    ) as week_start_date,\n        cast(\n\n    (-- Sunday as week start date\n    cast(\n        \n\n    (date_trunc('week', \n\n    (d.date_day + cast(1 as bigint) * interval 1 day)) + cast(-1 as bigint) * interval 1 day) as date\n    ) + cast(6 as bigint) * interval 1 day) as date) as week_end_date,\n        -- Sunday as week start date\n    cast(\n        \n\n    (date_trunc('week', \n\n    (d.prior_year_over_year_date_day + cast(1 as bigint) * interval 1 day)) + cast(-1 as bigint) * interval 1 day) as date\n    )\n        as prior_year_week_start_date,\n        cast(\n\n    (-- Sunday as week start date\n    cast(\n        \n\n    (date_trunc('week', \n\n    (d.prior_year_over_year_date_day + cast(1 as bigint) * interval 1 day)) + cast(-1 as bigint) * interval 1 day) as date\n    ) + cast(6 as bigint) * interval 1 day) as date)\n        as prior_year_week_end_date,\n        cast(ceil(dayofyear(d.date_day) / 7) as int) as week_of_year,\n\n        cast(date_trunc('week', d.date_day) as date) as iso_week_start_date,\n        cast(\n\n    (cast(date_trunc('week', d.date_day) as date) + cast(6 as bigint) * interval 1 day) as date) as iso_week_end_date,\n        cast(date_trunc('week', d.prior_year_over_year_date_day) as date)\n        as prior_year_iso_week_start_date,\n        cast(\n\n    (cast(date_trunc('week', d.prior_year_over_year_date_day) as date) + cast(6 as bigint) * interval 1 day) as date)\n        as prior_year_iso_week_end_date,\n        \n    cast(date_part('week', d.date_day) as integer) as iso_week_of_year,\n        case\n        when \n    cast(date_part('week', d.date_day) as integer) = 1\n        then\n            concat(\n                date_part('year', cast(\n\n    (cast(date_trunc('week', d.date_day) as date) + cast(6 as bigint) * interval 1 day) as date)),\n                '-W',\n                lpad(concat('',\n    cast(date_part('week', d.date_day) as integer)), 2, '0')\n            )\n        else\n            concat(\n                date_part('year', cast(date_trunc('week', d.date_day) as date)),\n                '-W',\n                lpad(concat('', \n    cast(date_part('week', d.date_day) as integer)), 2, '0')\n            )\n    end as iso_year_week,\n\n        cast(ceil(dayofyear(d.prior_year_over_year_date_day) / 7) as int)\n        as prior_year_week_of_year,\n        \n    cast(date_part('week', d.prior_year_over_year_date_day) as integer)\n        as prior_year_iso_week_of_year,\n\n        cast(\n            date_part('month', d.date_day) as integer\n        ) as month_of_year,\n        monthname(d.date_day) as month_name,\n        substr(monthname(d.date_day), 1, 3) as month_name_short,\n\n        cast(date_trunc('month', d.date_day) as date) as month_start_date,\n        cast(cast(\n        \n\n    (\n\n    (date_trunc('month', d.date_day) + cast(1 as bigint) * interval 1 month) + cast(-1 as bigint) * interval 1 day)\n        as date) as date) as month_end_date,\n\n        cast(\n            date_trunc('month', d.prior_year_date_day) as date\n        ) as prior_year_month_start_date,\n        cast(\n            cast(\n        \n\n    (\n\n    (date_trunc('month', d.prior_year_date_day) + cast(1 as bigint) * interval 1 month) + cast(-1 as bigint) * interval 1 day)\n        as date) as date\n        ) as prior_year_month_end_date,\n\n        cast(\n            date_part('quarter', d.date_day) as integer\n        ) as quarter_of_year,\n        cast(\n            date_trunc('quarter', d.date_day) as date\n        ) as quarter_start_date,\n        cast(-- duckdb dateadd does not support quarter interval.\n    cast(\n        \n\n    (\n\n    (date_trunc('quarter', d.date_day) + cast(3 as bigint) * interval 1 month) + cast(-1 as bigint) * interval 1 day)\n        as date) as date) as quarter_end_date,\n\n        cast(\n            date_part('year', d.date_day) as integer\n        ) as year_number,\n        cast(date_trunc('year', d.date_day) as date) as year_start_date,\n        cast(cast(\n        \n\n    (\n\n    (date_trunc('year', d.date_day) + cast(1 as bigint) * interval 1 year) + cast(-1 as bigint) * interval 1 day)\n        as date) as date) as year_end_date\n    from dates_with_prior_year_dates d\n    order by 1\n\n\n)","final":"final as (\n    select\n        -- surrogate key (YYYYMMDD format, valid for years up to 2147483)\n        cast(year_number * 10000 + month_of_year * 100 + day_of_month as integer) as date_key\n\n        -- actual date\n        , date_day as date_actual\n\n        -- day attributes (dbt_date convention: Sunday=1, Monday=2, ..., Saturday=7)\n        , day_of_week\n        , day_of_week_name as day_name\n        , day_of_week_name_short as day_name_short\n        , day_of_month\n        , day_of_year\n\n        -- week attributes\n        , week_of_year\n\n        -- month attributes\n        , month_of_year as month_actual\n        , month_name\n        , month_name_short\n\n        -- quarter attributes\n        , quarter_of_year as quarter_actual\n        , 'Q' || cast(quarter_of_year as varchar) as quarter_name\n\n        -- year attributes\n        , year_number as year_actual\n\n        -- flags (Sunday=1, Saturday=7 in dbt_date convention)\n        , case when day_of_week in (1, 7) then true else false end as is_weekend\n\n        -- us holidays (basic implementation, not comprehensive)\n        -- uses dbt_date convention: Sunday=1, Monday=2, Thursday=5, Saturday=7\n        , case\n            when month_of_year = 1 and day_of_month = 1 then true  -- new year's day\n            when month_of_year = 7 and day_of_month = 4 then true  -- independence day\n            when month_of_year = 12 and day_of_month = 25 then true  -- christmas\n            when month_of_year = 11 and day_of_week = 5\n                and day_of_month between 22 and 28 then true  -- thanksgiving (4th thursday)\n            when month_of_year = 1 and day_of_week = 2\n                and day_of_month between 15 and 21 then true  -- mlk day (3rd monday)\n            when month_of_year = 2 and day_of_week = 2\n                and day_of_month between 15 and 21 then true  -- presidents day (3rd monday)\n            when month_of_year = 5 and day_of_week = 2\n                and day_of_month between 25 and 31 then true  -- memorial day (last monday)\n            when month_of_year = 9 and day_of_week = 2\n                and day_of_month between 1 and 7 then true  -- labor day (1st monday)\n            when month_of_year = 11 and day_of_month = 11 then true  -- veterans day\n            else false\n        end as is_us_holiday\n\n        , case\n            when month_of_year = 1 and day_of_month = 1 then 'New Year''s Day'\n            when month_of_year = 7 and day_of_month = 4 then 'Independence Day'\n            when month_of_year = 12 and day_of_month = 25 then 'Christmas Day'\n            when month_of_year = 11 and day_of_week = 5\n                and day_of_month between 22 and 28 then 'Thanksgiving'\n            when month_of_year = 1 and day_of_week = 2\n                and day_of_month between 15 and 21 then 'Martin Luther King Jr. Day'\n            when month_of_year = 2 and day_of_week = 2\n                and day_of_month between 15 and 21 then 'Presidents Day'\n            when month_of_year = 5 and day_of_week = 2\n                and day_of_month between 25 and 31 then 'Memorial Day'\n            when month_of_year = 9 and day_of_week = 2\n                and day_of_month between 1 and 7 then 'Labor Day'\n            when month_of_year = 11 and day_of_month = 11 then 'Veterans Day'\n            else null\n        end as holiday_name\n\n    from date_spine\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='date_key'\n    )\n}}\n\n{#\n    Calendar dimension covering 1909-01-01 to 2025-12-31.\n\n    Note on date_key: Uses YYYYMMDD integer format. Valid range is years 0001-2147483\n    (integer max 2,147,483,647). Safe for all practical date ranges.\n\n    Note on day_of_week: dbt_date uses US convention (Sunday=1, Saturday=7),\n    NOT ISO 8601 (Monday=1). Weekend and holiday logic accounts for this.\n#}\n\nwith date_spine as (\n    {{ dbt_date.get_date_dimension('1909-01-01', '2025-12-31') }}\n),\n\nfinal as (\n    select\n        -- surrogate key (YYYYMMDD format, valid for years up to 2147483)\n        cast(year_number * 10000 + month_of_year * 100 + day_of_month as integer) as date_key\n\n        -- actual date\n        , date_day as date_actual\n\n        -- day attributes (dbt_date convention: Sunday=1, Monday=2, ..., Saturday=7)\n        , day_of_week\n        , day_of_week_name as day_name\n        , day_of_week_name_short as day_name_short\n        , day_of_month\n        , day_of_year\n\n        -- week attributes\n        , week_of_year\n\n        -- month attributes\n        , month_of_year as month_actual\n        , month_name\n        , month_name_short\n\n        -- quarter attributes\n        , quarter_of_year as quarter_actual\n        , 'Q' || cast(quarter_of_year as varchar) as quarter_name\n\n        -- year attributes\n        , year_number as year_actual\n\n        -- flags (Sunday=1, Saturday=7 in dbt_date convention)\n        , case when day_of_week in (1, 7) then true else false end as is_weekend\n\n        -- us holidays (basic implementation, not comprehensive)\n        -- uses dbt_date convention: Sunday=1, Monday=2, Thursday=5, Saturday=7\n        , case\n            when month_of_year = 1 and day_of_month = 1 then true  -- new year's day\n            when month_of_year = 7 and day_of_month = 4 then true  -- independence day\n            when month_of_year = 12 and day_of_month = 25 then true  -- christmas\n            when month_of_year = 11 and day_of_week = 5\n                and day_of_month between 22 and 28 then true  -- thanksgiving (4th thursday)\n            when month_of_year = 1 and day_of_week = 2\n                and day_of_month between 15 and 21 then true  -- mlk day (3rd monday)\n            when month_of_year = 2 and day_of_week = 2\n                and day_of_month between 15 and 21 then true  -- presidents day (3rd monday)\n            when month_of_year = 5 and day_of_week = 2\n                and day_of_month between 25 and 31 then true  -- memorial day (last monday)\n            when month_of_year = 9 and day_of_week = 2\n                and day_of_month between 1 and 7 then true  -- labor day (1st monday)\n            when month_of_year = 11 and day_of_month = 11 then true  -- veterans day\n            else false\n        end as is_us_holiday\n\n        , case\n            when month_of_year = 1 and day_of_month = 1 then 'New Year''s Day'\n            when month_of_year = 7 and day_of_month = 4 then 'Independence Day'\n            when month_of_year = 12 and day_of_month = 25 then 'Christmas Day'\n            when month_of_year = 11 and day_of_week = 5\n                and day_of_month between 22 and 28 then 'Thanksgiving'\n            when month_of_year = 1 and day_of_week = 2\n                and day_of_month between 15 and 21 then 'Martin Luther King Jr. Day'\n            when month_of_year = 2 and day_of_week = 2\n                and day_of_month between 15 and 21 then 'Presidents Day'\n            when month_of_year = 5 and day_of_week = 2\n                and day_of_month between 25 and 31 then 'Memorial Day'\n            when month_of_year = 9 and day_of_week = 2\n                and day_of_month between 1 and 7 then 'Labor Day'\n            when month_of_year = 11 and day_of_month = 11 then 'Veterans Day'\n            else null\n        end as holiday_name\n\n    from date_spine\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.dim_date","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_dim_date_date_key.0869fd48f9"]},"evidence":[{"label":"unique_key","value":"date_key"}],"pin_node":"(final select)"}]},{"name":"dim_organizations","path":"models/marts/core/dim_organizations.sql","description":"Organization dimension containing healthcare facilities. Includes an unknown member row (organization_key = -1) for handling missing lookups.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_organizations.sql","role":"final"}],"edges":[{"from":"source","to":"sequenced","edge_type":"from"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select * from unknown_member\n    union all\n    select * from sequenced\n)","sequenced":"sequenced as (\n    select\n        -- surrogate key (starting from 1, reserving -1 for unknown)\n        row_number() over (order by organization_id) as organization_key\n\n        -- natural key\n        , organization_id\n\n        -- attributes\n        , organization_name\n        , address\n        , city\n        , state\n        , zip_code\n        , phone\n\n        -- location\n        , latitude\n        , longitude\n\n        -- metrics\n        , revenue\n        , utilization\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main_staging\".\"stg_synthea__organizations\"\n)","unknown_member":"unknown_member as (\n    select\n        -1 as organization_key\n        , 'UNKNOWN' as organization_id\n        , 'Unknown Organization' as organization_name\n        , cast(null as varchar) as address\n        , cast(null as varchar) as city\n        , cast(null as varchar) as state\n        , cast(null as varchar) as zip_code\n        , cast(null as varchar) as phone\n        , cast(null as double) as latitude\n        , cast(null as double) as longitude\n        , cast(null as double) as revenue\n        , cast(null as bigint) as utilization\n        , current_timestamp as _loaded_at\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='organization_key'\n    )\n}}\n\nwith source as (\n    select * from {{ ref('stg_synthea__organizations') }}\n),\n\nsequenced as (\n    select\n        -- surrogate key (starting from 1, reserving -1 for unknown)\n        row_number() over (order by organization_id) as organization_key\n\n        -- natural key\n        , organization_id\n\n        -- attributes\n        , organization_name\n        , address\n        , city\n        , state\n        , zip_code\n        , phone\n\n        -- location\n        , latitude\n        , longitude\n\n        -- metrics\n        , revenue\n        , utilization\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from source\n),\n\n-- unknown member for handling missing dimension lookups\nunknown_member as (\n    select\n        -1 as organization_key\n        , 'UNKNOWN' as organization_id\n        , 'Unknown Organization' as organization_name\n        , cast(null as varchar) as address\n        , cast(null as varchar) as city\n        , cast(null as varchar) as state\n        , cast(null as varchar) as zip_code\n        , cast(null as varchar) as phone\n        , cast(null as double) as latitude\n        , cast(null as double) as longitude\n        , cast(null as double) as revenue\n        , cast(null as bigint) as utilization\n        , current_timestamp as _loaded_at\n),\n\nfinal as (\n    select * from unknown_member\n    union all\n    select * from sequenced\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.dim_organizations","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_dim_organizations_organization_key.096582bf56"]},"evidence":[{"label":"unique_key","value":"organization_key"}],"pin_node":"(final select)"},{"check":"union.arm-coverage","tier":"high","instrument":"unit-test","model_id":"model.healthcare_analytics.dim_organizations","construct":"union[final]","verdict":{"status":"uncovered"},"evidence":[{"label":"union","value":"final (2 arms: sequenced, unknown_member)"},{"label":"unexercised arm","value":"sequenced — no given row reaches ref('stg_synthea__organizations')"},{"label":"unattributable arm","value":"unknown_member — no resolvable upstream relation"}],"recommendation":"Add (or fill) a given row for each unexercised UNION arm's input so every arm contributes at least one row, then extend `expect` with the row(s) that arm should emit. This finding's evidence carries the per-arm input and a given-row sketch.","pin_node":"final","sketches":["- input: ref('stg_synthea__organizations')\n  rows:\n    - {_loaded_at: ..., address: ..., city: ..., latitude: ..., longitude: ..., organization_id: ..., organization_name: ..., phone: ..., revenue: ..., state: ..., utilization: ..., zip_code: ...}"]}]},{"name":"dim_patients","path":"models/marts/core/dim_patients.sql","description":"Patient dimension with SCD Type 2 history tracking. Each row represents a specific version of a patient's record. Includes an unknown member row (patient_key = -1) for handling missing lookups.\nSCD Type 2 columns: patient_key (surrogate), patient_id (natural), valid_from, valid_to, is_current.\n","dag":{"nodes":[{"id":"snapshot_source","role":"import"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_patients.sql","role":"final"}],"edges":[{"from":"snapshot_source","to":"sequenced","edge_type":"from"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select * from unknown_member\n    union all\n    select * from sequenced\n)","sequenced":"sequenced as (\n    select\n        -- surrogate key (unique per version, using dbt_scd_id for ordering)\n        row_number() over (order by dbt_scd_id) as patient_key\n\n        -- natural key\n        , patient_id\n\n        -- name attributes\n        , first_name\n        , last_name\n        , first_name || ' ' || last_name as full_name\n        , name_prefix\n        , name_suffix\n\n        -- dates\n        , birth_date\n        , death_date\n\n        -- derived age (current age or age at death)\n        , case\n            when death_date is not null\n            then date_diff('year', birth_date, death_date)\n            else date_diff('year', birth_date, current_date)\n        end as age_years\n\n        -- derived flags\n        , case when death_date is not null then true else false end as is_deceased\n\n        -- demographics\n        , gender\n        , race\n        , ethnicity\n        , marital_status\n\n        -- location\n        , address\n        , city\n        , state\n        , county\n        , zip_code\n        , latitude\n        , longitude\n\n        -- financial\n        , healthcare_expenses\n        , healthcare_coverage\n\n        -- scd type 2 columns from snapshot\n        , cast(dbt_valid_from as date) as valid_from\n        , cast(dbt_valid_to as date) as valid_to\n        , case when dbt_valid_to is null then true else false end as is_current\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from snapshot_source\n)","snapshot_source":"snapshot_source as (\n    -- source from snapshot for SCD2 history\n    -- falls back to staging if snapshot doesn't exist yet\n    \n        \n    \n\n    \n    -- fallback to staging if snapshot hasn't been run yet\n    select\n        patient_id\n        , first_name\n        , last_name\n        , name_prefix\n        , name_suffix\n        , gender\n        , race\n        , ethnicity\n        , marital_status\n        , birth_date\n        , death_date\n        , address\n        , city\n        , state\n        , county\n        , zip_code\n        , latitude\n        , longitude\n        , healthcare_expenses\n        , healthcare_coverage\n        -- mock SCD2 columns for initial state\n        , patient_id as dbt_scd_id\n        , birth_date as dbt_valid_from\n        , cast(null as timestamp) as dbt_valid_to\n    from \"memory\".\"main_staging\".\"stg_synthea__patients\"\n    \n)","unknown_member":"unknown_member as (\n    select\n        -1 as patient_key\n        , 'UNKNOWN' as patient_id\n        , 'Unknown' as first_name\n        , 'Patient' as last_name\n        , 'Unknown Patient' as full_name\n        , cast(null as varchar) as name_prefix\n        , cast(null as varchar) as name_suffix\n        , cast(null as date) as birth_date\n        , cast(null as date) as death_date\n        , cast(null as bigint) as age_years\n        , false as is_deceased\n        , cast(null as varchar) as gender\n        , cast(null as varchar) as race\n        , cast(null as varchar) as ethnicity\n        , cast(null as varchar) as marital_status\n        , cast(null as varchar) as address\n        , cast(null as varchar) as city\n        , cast(null as varchar) as state\n        , cast(null as varchar) as county\n        , cast(null as varchar) as zip_code\n        , cast(null as double) as latitude\n        , cast(null as double) as longitude\n        , cast(null as double) as healthcare_expenses\n        , cast(null as double) as healthcare_coverage\n        , cast('1900-01-01' as date) as valid_from\n        , cast(null as date) as valid_to\n        , true as is_current\n        , current_timestamp as _loaded_at\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='patient_key'\n    )\n}}\n\n-- depends_on: {{ ref('snp_patients') }}\n-- depends_on: {{ ref('stg_synthea__patients') }}\n\n{#\n    Patient Dimension with SCD Type 2 History Tracking\n\n    This dimension sources from the snp_patients snapshot, which tracks\n    changes to patient attributes over time. Each row represents a\n    specific version of a patient's record.\n\n    SCD Type 2 Columns:\n    - patient_key: Surrogate key (unique per version)\n    - patient_id: Natural key (same across versions)\n    - valid_from: When this version became active\n    - valid_to: When this version was superseded (null = current)\n    - is_current: True for the active version\n\n    To query current patients only:\n        WHERE is_current = true\n\n    To query patient state at a point in time:\n        WHERE valid_from <= @date AND (valid_to > @date OR valid_to IS NULL)\n#}\n\nwith snapshot_source as (\n    -- source from snapshot for SCD2 history\n    -- falls back to staging if snapshot doesn't exist yet\n    {% if execute %}\n        {% set snapshot_exists = adapter.get_relation(\n            database=target.database,\n            schema='snapshots',\n            identifier='snp_patients'\n        ) is not none %}\n    {% else %}\n        {% set snapshot_exists = false %}\n    {% endif %}\n\n    {% if snapshot_exists %}\n    select\n        patient_id\n        , first_name\n        , last_name\n        , name_prefix\n        , name_suffix\n        , gender\n        , race\n        , ethnicity\n        , marital_status\n        , birth_date\n        , death_date\n        , address\n        , city\n        , state\n        , county\n        , zip_code\n        , latitude\n        , longitude\n        , healthcare_expenses\n        , healthcare_coverage\n        -- snapshot SCD2 columns\n        , dbt_scd_id\n        , dbt_valid_from\n        , dbt_valid_to\n    from {{ ref('snp_patients') }}\n    {% else %}\n    -- fallback to staging if snapshot hasn't been run yet\n    select\n        patient_id\n        , first_name\n        , last_name\n        , name_prefix\n        , name_suffix\n        , gender\n        , race\n        , ethnicity\n        , marital_status\n        , birth_date\n        , death_date\n        , address\n        , city\n        , state\n        , county\n        , zip_code\n        , latitude\n        , longitude\n        , healthcare_expenses\n        , healthcare_coverage\n        -- mock SCD2 columns for initial state\n        , patient_id as dbt_scd_id\n        , birth_date as dbt_valid_from\n        , cast(null as timestamp) as dbt_valid_to\n    from {{ ref('stg_synthea__patients') }}\n    {% endif %}\n),\n\nsequenced as (\n    select\n        -- surrogate key (unique per version, using dbt_scd_id for ordering)\n        row_number() over (order by dbt_scd_id) as patient_key\n\n        -- natural key\n        , patient_id\n\n        -- name attributes\n        , first_name\n        , last_name\n        , first_name || ' ' || last_name as full_name\n        , name_prefix\n        , name_suffix\n\n        -- dates\n        , birth_date\n        , death_date\n\n        -- derived age (current age or age at death)\n        , case\n            when death_date is not null\n            then date_diff('year', birth_date, death_date)\n            else date_diff('year', birth_date, current_date)\n        end as age_years\n\n        -- derived flags\n        , case when death_date is not null then true else false end as is_deceased\n\n        -- demographics\n        , gender\n        , race\n        , ethnicity\n        , marital_status\n\n        -- location\n        , address\n        , city\n        , state\n        , county\n        , zip_code\n        , latitude\n        , longitude\n\n        -- financial\n        , healthcare_expenses\n        , healthcare_coverage\n\n        -- scd type 2 columns from snapshot\n        , cast(dbt_valid_from as date) as valid_from\n        , cast(dbt_valid_to as date) as valid_to\n        , case when dbt_valid_to is null then true else false end as is_current\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from snapshot_source\n),\n\n-- unknown member for handling missing dimension lookups\nunknown_member as (\n    select\n        -1 as patient_key\n        , 'UNKNOWN' as patient_id\n        , 'Unknown' as first_name\n        , 'Patient' as last_name\n        , 'Unknown Patient' as full_name\n        , cast(null as varchar) as name_prefix\n        , cast(null as varchar) as name_suffix\n        , cast(null as date) as birth_date\n        , cast(null as date) as death_date\n        , cast(null as bigint) as age_years\n        , false as is_deceased\n        , cast(null as varchar) as gender\n        , cast(null as varchar) as race\n        , cast(null as varchar) as ethnicity\n        , cast(null as varchar) as marital_status\n        , cast(null as varchar) as address\n        , cast(null as varchar) as city\n        , cast(null as varchar) as state\n        , cast(null as varchar) as county\n        , cast(null as varchar) as zip_code\n        , cast(null as double) as latitude\n        , cast(null as double) as longitude\n        , cast(null as double) as healthcare_expenses\n        , cast(null as double) as healthcare_coverage\n        , cast('1900-01-01' as date) as valid_from\n        , cast(null as date) as valid_to\n        , true as is_current\n        , current_timestamp as _loaded_at\n),\n\nfinal as (\n    select * from unknown_member\n    union all\n    select * from sequenced\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.dim_patients","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_dim_patients_patient_key.a372c8896a"]},"evidence":[{"label":"unique_key","value":"patient_key"}],"pin_node":"(final select)"},{"check":"union.arm-coverage","tier":"high","instrument":"unit-test","model_id":"model.healthcare_analytics.dim_patients","construct":"union[final]","verdict":{"status":"uncovered"},"evidence":[{"label":"union","value":"final (2 arms: sequenced, unknown_member)"},{"label":"unexercised arm","value":"sequenced — no given row reaches ref('stg_synthea__patients')"},{"label":"unattributable arm","value":"unknown_member — no resolvable upstream relation"}],"recommendation":"Add (or fill) a given row for each unexercised UNION arm's input so every arm contributes at least one row, then extend `expect` with the row(s) that arm should emit. This finding's evidence carries the per-arm input and a given-row sketch.","pin_node":"final","sketches":["- input: ref('stg_synthea__patients')\n  rows:\n    - {_loaded_at: ..., address: ..., birth_date: ..., birth_place: ..., city: ..., county: ..., death_date: ..., drivers_license: ..., ethnicity: ..., first_name: ..., gender: ..., healthcare_coverage: ..., healthcare_expenses: ..., last_name: ..., latitude: ..., longitude: ..., maiden_name: ..., marital_status: ..., name_prefix: ..., name_suffix: ..., passport_number: ..., patient_id: ..., race: ..., ssn_hash: ..., state: ..., zip_code: ...}"]}]},{"name":"dim_payers","path":"models/marts/core/dim_payers.sql","description":"Payer dimension containing insurance payers. Includes an unknown member row (payer_key = -1) for handling missing lookups.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_payers.sql","role":"final"}],"edges":[{"from":"source","to":"sequenced","edge_type":"from"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final\n\n-- ---------------------------------------------------------------------------\n-- cute-dbt dogfood (no-op): this trailing comment is the ONLY model change in\n-- the demo PR. It places dim_payers.sql in the PR diff so cute-dbt scopes the\n-- report to dim_payers + its unit test (test_dim_payers_injects_unknown_sentinel).\n-- ---------------------------------------------------------------------------\n\n-- cute-dbt fixture: synthetic body mod\n\n-- cute-dbt: ignore(union.arm-coverage, \"unknown_member is a constant sentinel arm, exercised by design\")","final":"final as (\n    select * from unknown_member\n    union all\n    select * from sequenced\n)","sequenced":"sequenced as (\n    select\n        -- surrogate key (starting from 1, reserving -1 for unknown)\n        row_number() over (order by payer_id) as payer_key\n\n        -- natural key\n        , payer_id\n\n        -- attributes\n        , payer_name\n        , address\n        , city\n        , state\n        , zip_code\n        , phone\n\n        -- financial metrics\n        , amount_covered\n        , amount_uncovered\n        , revenue\n\n        -- utilization metrics\n        , covered_encounters\n        , uncovered_encounters\n        , covered_medications\n        , uncovered_medications\n        , covered_procedures\n        , uncovered_procedures\n        , covered_immunizations\n        , uncovered_immunizations\n\n        -- member metrics\n        , unique_customers\n        , average_quality_of_life_score\n        , member_months\n\n        -- derived metrics\n        , case\n            when (amount_covered + amount_uncovered) > 0\n            then amount_covered / (amount_covered + amount_uncovered)\n            else 0\n        end as coverage_rate\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main_staging\".\"stg_synthea__payers\"\n)","unknown_member":"unknown_member as (\n    select\n        -1 as payer_key\n        , 'UNKNOWN' as payer_id\n        , 'Unknown Payer' as payer_name\n        , cast(null as varchar) as address\n        , cast(null as varchar) as city\n        , cast(null as varchar) as state\n        , cast(null as varchar) as zip_code\n        , cast(null as varchar) as phone\n        , cast(null as double) as amount_covered\n        , cast(null as double) as amount_uncovered\n        , cast(null as double) as revenue\n        , cast(null as bigint) as covered_encounters\n        , cast(null as bigint) as uncovered_encounters\n        , cast(null as bigint) as covered_medications\n        , cast(null as bigint) as uncovered_medications\n        , cast(null as bigint) as covered_procedures\n        , cast(null as bigint) as uncovered_procedures\n        , cast(null as bigint) as covered_immunizations\n        , cast(null as bigint) as uncovered_immunizations\n        , cast(null as bigint) as unique_customers\n        , cast(null as double) as average_quality_of_life_score\n        , cast(null as bigint) as member_months\n        , cast(null as double) as coverage_rate\n        , current_timestamp as _loaded_at\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='payer_key'\n    )\n}}\n\nwith source as (\n    select * from {{ ref('stg_synthea__payers') }}\n),\n\nsequenced as (\n    select\n        -- surrogate key (starting from 1, reserving -1 for unknown)\n        row_number() over (order by payer_id) as payer_key\n\n        -- natural key\n        , payer_id\n\n        -- attributes\n        , payer_name\n        , address\n        , city\n        , state\n        , zip_code\n        , phone\n\n        -- financial metrics\n        , amount_covered\n        , amount_uncovered\n        , revenue\n\n        -- utilization metrics\n        , covered_encounters\n        , uncovered_encounters\n        , covered_medications\n        , uncovered_medications\n        , covered_procedures\n        , uncovered_procedures\n        , covered_immunizations\n        , uncovered_immunizations\n\n        -- member metrics\n        , unique_customers\n        , average_quality_of_life_score\n        , member_months\n\n        -- derived metrics\n        , case\n            when (amount_covered + amount_uncovered) > 0\n            then amount_covered / (amount_covered + amount_uncovered)\n            else 0\n        end as coverage_rate\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from source\n),\n\n-- unknown member for handling missing dimension lookups\nunknown_member as (\n    select\n        -1 as payer_key\n        , 'UNKNOWN' as payer_id\n        , 'Unknown Payer' as payer_name\n        , cast(null as varchar) as address\n        , cast(null as varchar) as city\n        , cast(null as varchar) as state\n        , cast(null as varchar) as zip_code\n        , cast(null as varchar) as phone\n        , cast(null as double) as amount_covered\n        , cast(null as double) as amount_uncovered\n        , cast(null as double) as revenue\n        , cast(null as bigint) as covered_encounters\n        , cast(null as bigint) as uncovered_encounters\n        , cast(null as bigint) as covered_medications\n        , cast(null as bigint) as uncovered_medications\n        , cast(null as bigint) as covered_procedures\n        , cast(null as bigint) as uncovered_procedures\n        , cast(null as bigint) as covered_immunizations\n        , cast(null as bigint) as uncovered_immunizations\n        , cast(null as bigint) as unique_customers\n        , cast(null as double) as average_quality_of_life_score\n        , cast(null as bigint) as member_months\n        , cast(null as double) as coverage_rate\n        , current_timestamp as _loaded_at\n),\n\nfinal as (\n    select * from unknown_member\n    union all\n    select * from sequenced\n)\n\nselect * from final\n\n-- ---------------------------------------------------------------------------\n-- cute-dbt dogfood (no-op): this trailing comment is the ONLY model change in\n-- the demo PR. It places dim_payers.sql in the PR diff so cute-dbt scopes the\n-- report to dim_payers + its unit test (test_dim_payers_injects_unknown_sentinel).\n-- ---------------------------------------------------------------------------\n\n-- cute-dbt fixture: synthetic body mod\n\n-- cute-dbt: ignore(union.arm-coverage, \"unknown_member is a constant sentinel arm, exercised by design\")","tests":[{"id":"unit_test.healthcare_analytics.dim_payers.test_dim_payers_injects_unknown_sentinel","name":"test_dim_payers_injects_unknown_sentinel","target_model":"dim_payers","changed":false,"description":"dim_payers UNION-ALLs an unknown-member sentinel row (payer_key = -1)\nwith the sequenced source rows. This test verifies the sentinel\nsurvives the union and the sequenced rows are surrogate-keyed\nstarting at 1. Uses dbt's dict format for both GIVEN and EXPECT —\ndict format only compares listed columns, so non-deterministic\noutputs (`_loaded_at` via `current_timestamp`) are excluded from\nassertion automatically.\n","tags":[],"meta":{},"defined_in":"models/marts/core/_core__models.yml","given":[{"input":"ref('stg_synthea__payers')","bound_to_node":"source","table":{"columns":["address","amount_covered","amount_uncovered","average_quality_of_life_score","city","covered_encounters","covered_immunizations","covered_medications","covered_procedures","member_months","payer_id","payer_name","phone","revenue","state","uncovered_encounters","uncovered_immunizations","uncovered_medications","uncovered_procedures","unique_customers","zip_code"],"rows":[{"cells":[{"display":"1 Acme Way","key":{"t":"str","v":"1 Acme Way"}},{"display":"1000.0","key":{"t":"number","v":"1000"}},{"display":"250.0","key":{"t":"number","v":"250"}},{"display":"0.85","key":{"t":"number","v":"0.85"}},{"display":"Boston","key":{"t":"str","v":"Boston"}},{"display":"10","key":{"t":"number","v":"10"}},{"display":"4","key":{"t":"number","v":"4"}},{"display":"5","key":{"t":"number","v":"5"}},{"display":"3","key":{"t":"number","v":"3"}},{"display":"96","key":{"t":"number","v":"96"}},{"display":"a00000aa-0000-0000-0000-000000000001","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000001"}},{"display":"Acme Health","key":{"t":"str","v":"Acme Health"}},{"display":"555-0100","key":{"t":"str","v":"555-0100"}},{"display":"1250.0","key":{"t":"number","v":"1250"}},{"display":"MA","key":{"t":"str","v":"MA"}},{"display":"2","key":{"t":"number","v":"2"}},{"display":"0","key":{"t":"number","v":"0"}},{"display":"1","key":{"t":"number","v":"1"}},{"display":"0","key":{"t":"number","v":"0"}},{"display":"8","key":{"t":"number","v":"8"}},{"display":"02101","key":{"t":"str","v":"02101"}}]}]},"rows":[{"address":"1 Acme Way","amount_covered":1000.0,"amount_uncovered":250.0,"average_quality_of_life_score":0.85,"city":"Boston","covered_encounters":10,"covered_immunizations":4,"covered_medications":5,"covered_procedures":3,"member_months":96,"payer_id":"a00000aa-0000-0000-0000-000000000001","payer_name":"Acme Health","phone":"555-0100","revenue":1250.0,"state":"MA","uncovered_encounters":2,"uncovered_immunizations":0,"uncovered_medications":1,"uncovered_procedures":0,"unique_customers":8,"zip_code":"02101"}],"format":"dict","column_meta":{"address":{"description":"Street address"},"amount_covered":{"description":"Total amount covered by payer","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},"amount_uncovered":{"description":"Total amount not covered by payer"},"average_quality_of_life_score":{"description":"Average quality of life score for members"},"city":{"description":"City"},"covered_encounters":{"description":"Number of encounters covered"},"covered_immunizations":{"description":"Number of immunizations covered"},"covered_medications":{"description":"Number of medications covered"},"covered_procedures":{"description":"Number of procedures covered"},"member_months":{"description":"Total member months"},"payer_id":{"description":"Unique payer identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},"payer_name":{"description":"Name of the insurance payer","tests":[{"name":"not null"}]},"phone":{"description":"Phone number"},"revenue":{"description":"Total revenue collected","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},"state":{"description":"State where headquartered"},"uncovered_encounters":{"description":"Number of encounters not covered"},"uncovered_immunizations":{"description":"Number of immunizations not covered"},"uncovered_medications":{"description":"Number of medications not covered"},"uncovered_procedures":{"description":"Number of procedures not covered"},"unique_customers":{"description":"Number of unique customers"},"zip_code":{"description":"ZIP code (stored as numeric, 5 digits)"}}}],"expected":{"table":{"columns":["payer_id","payer_key","payer_name"],"rows":[{"cells":[{"display":"UNKNOWN","key":{"t":"str","v":"UNKNOWN"}},{"display":"-1","key":{"t":"number","v":"-1"}},{"display":"Unknown Payer","key":{"t":"str","v":"Unknown Payer"}}]},{"cells":[{"display":"a00000aa-0000-0000-0000-000000000001","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000001"}},{"display":"1","key":{"t":"number","v":"1"}},{"display":"Acme Health","key":{"t":"str","v":"Acme Health"}}]}]},"rows":[{"payer_id":"UNKNOWN","payer_key":-1,"payer_name":"Unknown Payer"},{"payer_id":"a00000aa-0000-0000-0000-000000000001","payer_key":1,"payer_name":"Acme Health"}],"format":"dict","column_meta":{"payer_id":{"description":"Natural payer identifier (UUID)","tests":[{"name":"not null"}]},"payer_key":{"description":"Surrogate key (-1 for unknown member)","tests":[{"name":"not null"},{"name":"unique"}]},"payer_name":{"description":"Name of the insurance payer","tests":[{"name":"not null"}]}}}}],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.dim_payers","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_dim_payers_payer_key.953b1f5fd2"]},"evidence":[{"label":"unique_key","value":"payer_key"}],"pin_node":"(final select)"},{"check":"union.arm-coverage","tier":"high","instrument":"unit-test","model_id":"model.healthcare_analytics.dim_payers","construct":"union[final]","verdict":{"status":"unknown"},"evidence":[{"label":"union","value":"final (2 arms: sequenced, unknown_member)"},{"label":"unattributable arm","value":"unknown_member — no resolvable upstream relation"}],"pin_node":"final"}]},{"name":"dim_providers","path":"models/marts/core/dim_providers.sql","description":"Provider dimension containing healthcare providers (doctors, nurses, etc.). Includes an unknown member row (provider_key = -1) for handling missing lookups.\n","dag":{"nodes":[{"id":"providers","role":"import"},{"id":"organizations","role":"import"},{"id":"sequenced","role":"transform"},{"id":"unknown_member","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"dim_providers.sql","role":"final"}],"edges":[{"from":"providers","to":"sequenced","edge_type":"from"},{"from":"organizations","to":"sequenced","edge_type":"left"},{"from":"unknown_member","to":"final","edge_type":"union_all"},{"from":"sequenced","to":"final","edge_type":"union_all"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select * from unknown_member\n    union all\n    select * from sequenced\n)","organizations":"organizations as (\n    select\n        organization_key\n        , organization_id\n    from \"memory\".\"main_marts\".\"dim_organizations\"\n)","providers":"providers as (\n    select * from \"memory\".\"main_staging\".\"stg_synthea__providers\"\n)","sequenced":"sequenced as (\n    select\n        -- surrogate key (starting from 1, reserving -1 for unknown)\n        row_number() over (order by p.provider_id) as provider_key\n\n        -- natural key\n        , p.provider_id\n\n        -- organization foreign key\n        , o.organization_key\n        , p.organization_id\n\n        -- attributes\n        , p.provider_name\n        , p.gender\n        , p.specialty\n\n        -- location\n        , p.address\n        , p.city\n        , p.state\n        , p.zip_code\n        , p.latitude\n        , p.longitude\n\n        -- metrics\n        , p.utilization\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from providers p\n    left join organizations o\n        on p.organization_id = o.organization_id\n)","unknown_member":"unknown_member as (\n    select\n        -1 as provider_key\n        , 'UNKNOWN' as provider_id\n        , -1 as organization_key\n        , 'UNKNOWN' as organization_id\n        , 'Unknown Provider' as provider_name\n        , cast(null as varchar) as gender\n        , cast(null as varchar) as specialty\n        , cast(null as varchar) as address\n        , cast(null as varchar) as city\n        , cast(null as varchar) as state\n        , cast(null as varchar) as zip_code\n        , cast(null as double) as latitude\n        , cast(null as double) as longitude\n        , cast(null as bigint) as utilization\n        , current_timestamp as _loaded_at\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='provider_key'\n    )\n}}\n\nwith providers as (\n    select * from {{ ref('stg_synthea__providers') }}\n),\n\norganizations as (\n    select\n        organization_key\n        , organization_id\n    from {{ ref('dim_organizations') }}\n),\n\nsequenced as (\n    select\n        -- surrogate key (starting from 1, reserving -1 for unknown)\n        row_number() over (order by p.provider_id) as provider_key\n\n        -- natural key\n        , p.provider_id\n\n        -- organization foreign key\n        , o.organization_key\n        , p.organization_id\n\n        -- attributes\n        , p.provider_name\n        , p.gender\n        , p.specialty\n\n        -- location\n        , p.address\n        , p.city\n        , p.state\n        , p.zip_code\n        , p.latitude\n        , p.longitude\n\n        -- metrics\n        , p.utilization\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from providers p\n    left join organizations o\n        on p.organization_id = o.organization_id\n),\n\n-- unknown member for handling missing dimension lookups\nunknown_member as (\n    select\n        -1 as provider_key\n        , 'UNKNOWN' as provider_id\n        , -1 as organization_key\n        , 'UNKNOWN' as organization_id\n        , 'Unknown Provider' as provider_name\n        , cast(null as varchar) as gender\n        , cast(null as varchar) as specialty\n        , cast(null as varchar) as address\n        , cast(null as varchar) as city\n        , cast(null as varchar) as state\n        , cast(null as varchar) as zip_code\n        , cast(null as double) as latitude\n        , cast(null as double) as longitude\n        , cast(null as bigint) as utilization\n        , current_timestamp as _loaded_at\n),\n\nfinal as (\n    select * from unknown_member\n    union all\n    select * from sequenced\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.dim_providers","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_dim_providers_provider_key.02ac65c919"]},"evidence":[{"label":"unique_key","value":"provider_key"}],"pin_node":"(final select)"},{"check":"union.arm-coverage","tier":"high","instrument":"unit-test","model_id":"model.healthcare_analytics.dim_providers","construct":"union[final]","verdict":{"status":"uncovered"},"evidence":[{"label":"union","value":"final (2 arms: sequenced, unknown_member)"},{"label":"unexercised arm","value":"sequenced — no given row reaches ref('dim_organizations'), ref('stg_synthea__providers')"},{"label":"unattributable arm","value":"unknown_member — no resolvable upstream relation"}],"recommendation":"Add (or fill) a given row for each unexercised UNION arm's input so every arm contributes at least one row, then extend `expect` with the row(s) that arm should emit. This finding's evidence carries the per-arm input and a given-row sketch.","pin_node":"final","sketches":["- input: ref('dim_organizations')\n  rows:\n    - {_loaded_at: ..., address: ..., city: ..., latitude: ..., longitude: ..., organization_id: ..., organization_key: ..., organization_name: ..., phone: ..., revenue: ..., state: ..., utilization: ..., zip_code: ...}\n- input: ref('stg_synthea__providers')\n  rows:\n    - {_loaded_at: ..., address: ..., city: ..., gender: ..., latitude: ..., longitude: ..., organization_id: ..., provider_id: ..., provider_name: ..., specialty: ..., state: ..., utilization: ..., zip_code: ...}"]},{"check":"join.left-null-propagation","tier":"high","instrument":"both","model_id":"model.healthcare_analytics.dim_providers","construct":"left_join[sequenced:organizations]","verdict":{"status":"uncovered"},"evidence":[{"label":"left join","value":"sequenced — LEFT JOIN organizations ON providers.organization_id = organizations.organization_id"}],"recommendation":"Add a no-match given: one left-side row whose join key is absent from the right-side given rows, then extend `expect` with that row carrying NULL right-side columns (or the intended fallback). This finding's evidence carries a copy-pasteable given sketch.","pin_node":"sequenced","sketches":["- input: ref('stg_synthea__providers')\n  rows:\n    - {organization_id: 404}   # 404 has no match below — the no-match path\n- input: ref('dim_organizations')\n  rows:\n    - {organization_id: 1}\n# expect: the no-match row with NULL dim_organizations columns (or the intended fallback)"]}]},{"name":"fct_clinical_events","path":"models/marts/core/fct_clinical_events.sql","description":"Unified clinical events fact table combining conditions, medications, and procedures. Each row represents a single clinical event with standardized structure. Links to patient and encounter dimensions.\n","dag":{"nodes":[{"id":"valid_encounters","role":"import"},{"id":"conditions","role":"import"},{"id":"medications","role":"import"},{"id":"procedures","role":"import"},{"id":"all_events","role":"transform"},{"id":"patients","role":"import"},{"id":"dim_date","role":"import"},{"id":"encounters","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_clinical_events.sql","role":"final"}],"edges":[{"from":"conditions","to":"all_events","edge_type":"union_all"},{"from":"medications","to":"all_events","edge_type":"union_all"},{"from":"procedures","to":"all_events","edge_type":"union_all"},{"from":"all_events","to":"final","edge_type":"from"},{"from":"patients","to":"final","edge_type":"left"},{"from":"encounters","to":"final","edge_type":"left"},{"from":"dim_date","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final\n\n-- cute-dbt fixture: synthetic body mod","all_events":"all_events as (\n    select * from conditions\n    union all\n    select * from medications\n    union all\n    select * from procedures\n)","conditions":"conditions as (\n    select\n        condition_id as event_id\n        , 'CONDITION' as event_type\n        , patient_id\n        , cond.encounter_id\n        , condition_start_date as event_start_date\n        , condition_end_date as event_end_date\n        , condition_code as code\n        , 'SNOMED-CT' as code_system\n        , condition_description as description\n        , cast(null as varchar) as reason_code\n        , cast(null as varchar) as reason_description\n        , cast(null as decimal(18, 2)) as event_cost\n    from \"memory\".\"main_staging\".\"stg_synthea__conditions\" as cond\n    where cond.encounter_id in (select encounter_id from valid_encounters)\n)","dim_date":"dim_date as (\n    select\n        date_key\n        , date_actual\n    from \"memory\".\"main_marts\".\"dim_date\"\n)","encounters":"encounters as (\n    select\n        encounter_key\n        , encounter_id\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n)","final":"final as (\n    select\n        -- surrogate key\n        row_number() over (order by e.event_id) as clinical_event_key\n\n        -- event identifiers\n        , e.event_type\n        , e.event_id\n\n        -- dimension keys\n        , coalesce(p.patient_key, -1) as patient_key\n        , e.patient_id\n        , coalesce(enc.encounter_key, -1) as encounter_key\n        , e.encounter_id\n        , coalesce(d.date_key, -1) as event_date_key\n\n        -- dates\n        , e.event_start_date\n        , e.event_end_date\n\n        -- code information\n        , e.code\n        , e.code_system\n        , e.description\n\n        -- reason\n        , e.reason_code\n        , e.reason_description\n\n        -- cost\n        , e.event_cost\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from all_events as e\n    left join patients as p on e.patient_id = p.patient_id\n    left join encounters as enc on e.encounter_id = enc.encounter_id\n    left join dim_date as d on e.event_start_date = d.date_actual\n)","medications":"medications as (\n    select\n        medication_id as event_id\n        , 'MEDICATION' as event_type\n        , patient_id\n        , med.encounter_id\n        , cast(medication_start_at as date) as event_start_date\n        , cast(medication_end_at as date) as event_end_date\n        , medication_code as code\n        , 'RXNORM' as code_system\n        , medication_description as description\n        , reason_code\n        , reason_description\n        , total_cost as event_cost\n    from \"memory\".\"main_staging\".\"stg_synthea__medications\" as med\n    \n    \n    where is_dq_valid = true\n    \n\n    and med.encounter_id in (select encounter_id from valid_encounters)\n)","patients":"patients as (\n    select\n        patient_key\n        , patient_id\n    from \"memory\".\"main_marts\".\"dim_patients\"\n    where is_current = true\n)","procedures":"procedures as (\n    select\n        procedure_id as event_id\n        , 'PROCEDURE' as event_type\n        , patient_id\n        , proc.encounter_id\n        , cast(procedure_at as date) as event_start_date\n        , cast(null as date) as event_end_date\n        , procedure_code as code\n        , 'SNOMED-CT' as code_system\n        , procedure_description as description\n        , reason_code\n        , reason_description\n        , base_cost as event_cost\n    from \"memory\".\"main_staging\".\"stg_synthea__procedures\" as proc\n    where proc.encounter_id in (select encounter_id from valid_encounters)\n)","valid_encounters":"valid_encounters as (\n    select encounter_id\n    from \"memory\".\"main_staging\".\"stg_synthea__encounters\"\n    \n    \n    where is_dq_valid = true\n    \n\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='clinical_event_key'\n    )\n}}\n\nwith valid_encounters as (\n    select encounter_id\n    from {{ ref('stg_synthea__encounters') }}\n    {{ quarantine_filter() }}\n),\n\nconditions as (\n    select\n        condition_id as event_id\n        , 'CONDITION' as event_type\n        , patient_id\n        , cond.encounter_id\n        , condition_start_date as event_start_date\n        , condition_end_date as event_end_date\n        , condition_code as code\n        , 'SNOMED-CT' as code_system\n        , condition_description as description\n        , cast(null as varchar) as reason_code\n        , cast(null as varchar) as reason_description\n        , cast(null as decimal(18, 2)) as event_cost\n    from {{ ref('stg_synthea__conditions') }} as cond\n    where cond.encounter_id in (select encounter_id from valid_encounters)\n),\n\nmedications as (\n    select\n        medication_id as event_id\n        , 'MEDICATION' as event_type\n        , patient_id\n        , med.encounter_id\n        , cast(medication_start_at as date) as event_start_date\n        , cast(medication_end_at as date) as event_end_date\n        , medication_code as code\n        , 'RXNORM' as code_system\n        , medication_description as description\n        , reason_code\n        , reason_description\n        , total_cost as event_cost\n    from {{ ref('stg_synthea__medications') }} as med\n    {{ quarantine_filter() }}\n    and med.encounter_id in (select encounter_id from valid_encounters)\n),\n\nprocedures as (\n    select\n        procedure_id as event_id\n        , 'PROCEDURE' as event_type\n        , patient_id\n        , proc.encounter_id\n        , cast(procedure_at as date) as event_start_date\n        , cast(null as date) as event_end_date\n        , procedure_code as code\n        , 'SNOMED-CT' as code_system\n        , procedure_description as description\n        , reason_code\n        , reason_description\n        , base_cost as event_cost\n    from {{ ref('stg_synthea__procedures') }} as proc\n    where proc.encounter_id in (select encounter_id from valid_encounters)\n),\n\nall_events as (\n    select * from conditions\n    union all\n    select * from medications\n    union all\n    select * from procedures\n),\n\npatients as (\n    select\n        patient_key\n        , patient_id\n    from {{ ref('dim_patients') }}\n    where is_current = true\n),\n\ndim_date as (\n    select\n        date_key\n        , date_actual\n    from {{ ref('dim_date') }}\n),\n\nencounters as (\n    select\n        encounter_key\n        , encounter_id\n    from {{ ref('fct_encounters') }}\n),\n\nfinal as (\n    select\n        -- surrogate key\n        row_number() over (order by e.event_id) as clinical_event_key\n\n        -- event identifiers\n        , e.event_type\n        , e.event_id\n\n        -- dimension keys\n        , coalesce(p.patient_key, -1) as patient_key\n        , e.patient_id\n        , coalesce(enc.encounter_key, -1) as encounter_key\n        , e.encounter_id\n        , coalesce(d.date_key, -1) as event_date_key\n\n        -- dates\n        , e.event_start_date\n        , e.event_end_date\n\n        -- code information\n        , e.code\n        , e.code_system\n        , e.description\n\n        -- reason\n        , e.reason_code\n        , e.reason_description\n\n        -- cost\n        , e.event_cost\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from all_events as e\n    left join patients as p on e.patient_id = p.patient_id\n    left join encounters as enc on e.encounter_id = enc.encounter_id\n    left join dim_date as d on e.event_start_date = d.date_actual\n)\n\nselect * from final\n\n-- cute-dbt fixture: synthetic body mod","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_clinical_events","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_fct_clinical_events_clinical_event_key.2af827606b"]},"evidence":[{"label":"unique_key","value":"clinical_event_key"}],"pin_node":"(final select)"},{"check":"union.arm-coverage","tier":"high","instrument":"unit-test","model_id":"model.healthcare_analytics.fct_clinical_events","construct":"union[all_events]","verdict":{"status":"uncovered"},"evidence":[{"label":"union","value":"all_events (3 arms: conditions, medications, procedures)"},{"label":"unexercised arm","value":"conditions — no given row reaches ref('stg_synthea__conditions')"},{"label":"unexercised arm","value":"medications — no given row reaches ref('stg_synthea__medications')"},{"label":"unexercised arm","value":"procedures — no given row reaches ref('stg_synthea__procedures')"}],"recommendation":"Add (or fill) a given row for each unexercised UNION arm's input so every arm contributes at least one row, then extend `expect` with the row(s) that arm should emit. This finding's evidence carries the per-arm input and a given-row sketch.","pin_node":"all_events","sketches":["- input: ref('stg_synthea__conditions')\n  rows:\n    - {_loaded_at: ..., condition_code: ..., condition_description: ..., condition_end_date: ..., condition_id: ..., condition_start_date: ..., encounter_id: ..., patient_id: ...}","- input: ref('stg_synthea__medications')\n  rows:\n    - {_loaded_at: ..., base_cost: ..., dispenses: ..., encounter_id: ..., medication_code: ..., medication_description: ..., medication_end_at: ..., medication_id: ..., medication_start_at: ..., patient_id: ..., payer_coverage: ..., payer_id: ..., reason_code: ..., reason_description: ..., total_cost: ...}","- input: ref('stg_synthea__procedures')\n  rows:\n    - {_loaded_at: ..., base_cost: ..., encounter_id: ..., patient_id: ..., procedure_at: ..., procedure_code: ..., procedure_description: ..., procedure_id: ..., reason_code: ..., reason_description: ...}"]}]},{"name":"fct_condition_cohorts","path":"models/marts/analytics/fct_condition_cohorts.sql","description":"Patient-condition cohort analysis for disease management and population health.\nOne row per unique patient-condition combination with timeline and encounter details.\nGrain: (patient_id, condition_code)\n\nUse cases:\n- Disease management program enrollment\n- Cohort identification for clinical trials\n- Chronic condition tracking\n- Care gap analysis\n- Risk stratification by condition\n","dag":{"nodes":[{"id":"conditions_source","role":"import"},{"id":"patients","role":"import"},{"id":"dim_conditions","role":"import"},{"id":"condition_windows","role":"transform"},{"id":"with_dimensions","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_condition_cohorts.sql","role":"final"}],"edges":[{"from":"conditions_source","to":"condition_windows","edge_type":"from"},{"from":"condition_windows","to":"with_dimensions","edge_type":"from"},{"from":"patients","to":"with_dimensions","edge_type":"left"},{"from":"dim_conditions","to":"with_dimensions","edge_type":"left"},{"from":"with_dimensions","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","condition_windows":"condition_windows as (\n    select\n        patient_id\n        , condition_code\n        , max(condition_description) as condition_description\n        , min(condition_start_date) as first_diagnosis_date\n        , max(condition_end_date) as last_diagnosis_date\n        , count(distinct encounter_id) as encounter_count\n        -- if any occurrence has no end date, condition is considered active\n        , count(case when condition_end_date is null then 1 end) > 0 as is_active\n    from conditions_source\n    group by patient_id, condition_code\n)","conditions_source":"conditions_source as (\n    select\n        patient_id\n        , encounter_id\n        -- cast to varchar for consistent handling (source is BIGINT SNOMED codes)\n        , cast(condition_code as varchar) as condition_code\n        , condition_description\n        , condition_start_date\n        , condition_end_date\n    from \"memory\".\"main_staging\".\"stg_synthea__conditions\"\n    where condition_code is not null\n      and patient_id is not null\n)","dim_conditions":"dim_conditions as (\n    select\n        condition_key\n        , condition_code\n    from \"memory\".\"main_marts\".\"dim_conditions\"\n)","final":"final as (\n    select\n        -- surrogate key\n        md5(cast(patient_id as varchar) || '-' || condition_code) as condition_cohort_key\n\n        -- dimension keys\n        , patient_key\n        , patient_id\n        , condition_key\n        , condition_code\n\n        -- condition details\n        , condition_description\n\n        -- date dimensions\n        , first_diagnosis_date\n        , last_diagnosis_date\n        , extract(year from first_diagnosis_date) as first_diagnosis_year\n\n        -- measures: duration\n        , case\n            when last_diagnosis_date is not null and first_diagnosis_date is not null\n            then greatest(\n                0,\n                (extract(year from last_diagnosis_date) - extract(year from first_diagnosis_date)) * 12\n                + (extract(month from last_diagnosis_date) - extract(month from first_diagnosis_date))\n            )\n            else 0\n        end as months_with_condition\n\n        -- measures: counts\n        , encounter_count\n\n        -- measures: status\n        , is_active\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from with_dimensions\n)","patients":"patients as (\n    select\n        patient_key\n        , patient_id\n    from \"memory\".\"main_marts\".\"dim_patients\"\n    where is_current = true\n)","with_dimensions":"with_dimensions as (\n    select\n        cw.patient_id\n        , cw.condition_code\n        , cw.condition_description\n        , cw.first_diagnosis_date\n        , cw.last_diagnosis_date\n        , cw.encounter_count\n        , cw.is_active\n        , coalesce(p.patient_key, -1) as patient_key\n        , coalesce(dc.condition_key, -1) as condition_key\n    from condition_windows as cw\n    left join patients as p on cw.patient_id = p.patient_id\n    left join dim_conditions as dc on cw.condition_code = dc.condition_code\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='condition_cohort_key',\n        tags=['analytics', 'marts', 'fact']\n    )\n}}\n\n{#\n    Patient-Condition Cohort Fact\n\n    Purpose: Patient-condition relationships for disease management and outcomes analysis\n    Grain: One row per patient-condition combination (first occurrence)\n    Use cases: Disease management, outcomes by condition, cohort analysis\n\n    Aggregates condition occurrences by patient to show:\n    - First and last diagnosis dates\n    - Duration of condition\n    - Number of encounters with the condition\n    - Active status (no end date = currently active)\n#}\n\nwith conditions_source as (\n    select\n        patient_id\n        , encounter_id\n        -- cast to varchar for consistent handling (source is BIGINT SNOMED codes)\n        , cast(condition_code as varchar) as condition_code\n        , condition_description\n        , condition_start_date\n        , condition_end_date\n    from {{ ref('stg_synthea__conditions') }}\n    where condition_code is not null\n      and patient_id is not null\n),\n\npatients as (\n    select\n        patient_key\n        , patient_id\n    from {{ ref('dim_patients') }}\n    where is_current = true\n),\n\ndim_conditions as (\n    select\n        condition_key\n        , condition_code\n    from {{ ref('dim_conditions') }}\n),\n\n-- aggregate conditions by patient and condition code\ncondition_windows as (\n    select\n        patient_id\n        , condition_code\n        , max(condition_description) as condition_description\n        , min(condition_start_date) as first_diagnosis_date\n        , max(condition_end_date) as last_diagnosis_date\n        , count(distinct encounter_id) as encounter_count\n        -- if any occurrence has no end date, condition is considered active\n        , count(case when condition_end_date is null then 1 end) > 0 as is_active\n    from conditions_source\n    group by patient_id, condition_code\n),\n\n-- join to dimensions\nwith_dimensions as (\n    select\n        cw.patient_id\n        , cw.condition_code\n        , cw.condition_description\n        , cw.first_diagnosis_date\n        , cw.last_diagnosis_date\n        , cw.encounter_count\n        , cw.is_active\n        , coalesce(p.patient_key, -1) as patient_key\n        , coalesce(dc.condition_key, -1) as condition_key\n    from condition_windows as cw\n    left join patients as p on cw.patient_id = p.patient_id\n    left join dim_conditions as dc on cw.condition_code = dc.condition_code\n),\n\nfinal as (\n    select\n        -- surrogate key\n        md5(cast(patient_id as varchar) || '-' || condition_code) as condition_cohort_key\n\n        -- dimension keys\n        , patient_key\n        , patient_id\n        , condition_key\n        , condition_code\n\n        -- condition details\n        , condition_description\n\n        -- date dimensions\n        , first_diagnosis_date\n        , last_diagnosis_date\n        , extract(year from first_diagnosis_date) as first_diagnosis_year\n\n        -- measures: duration\n        , case\n            when last_diagnosis_date is not null and first_diagnosis_date is not null\n            then greatest(\n                0,\n                (extract(year from last_diagnosis_date) - extract(year from first_diagnosis_date)) * 12\n                + (extract(month from last_diagnosis_date) - extract(month from first_diagnosis_date))\n            )\n            else 0\n        end as months_with_condition\n\n        -- measures: counts\n        , encounter_count\n\n        -- measures: status\n        , is_active\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from with_dimensions\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_condition_cohorts","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_fct_condition_cohorts_condition_cohort_key.f8c8f721d9"]},"evidence":[{"label":"unique_key","value":"condition_cohort_key"}],"pin_node":"(final select)"}]},{"name":"fct_cost_analysis","path":"models/marts/analytics/fct_cost_analysis.sql","description":"Detailed cost breakdown for financial analysis and revenue cycle management.\nOne row per encounter with cost allocation details across payer and patient.\nGrain: encounter_id\n\nUse cases:\n- Financial performance reporting\n- Payer mix analysis\n- Patient out-of-pocket tracking\n- Cost driver identification\n- Revenue cycle optimization\n","dag":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"procedures","role":"import"},{"id":"encounters_enriched","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_cost_analysis.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_enriched","edge_type":"from"},{"from":"dim_date","to":"encounters_enriched","edge_type":"left"},{"from":"procedures","to":"encounters_enriched","edge_type":"left"},{"from":"encounters_enriched","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","dim_date":"dim_date as (\n    select\n        date_key\n        , date_actual\n        , year_actual\n    from \"memory\".\"main_marts\".\"dim_date\"\n)","encounters":"encounters as (\n    select\n        encounter_key\n        , encounter_id\n        , patient_key\n        , patient_id\n        , payer_key\n        , payer_id\n        , provider_key\n        , provider_id\n        , encounter_start_date_key\n        , encounter_class\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , encounter_start_at\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n)","encounters_enriched":"encounters_enriched as (\n    select\n        e.encounter_key\n        , e.encounter_id\n        , e.patient_key\n        , e.patient_id\n        , e.payer_key\n        , e.payer_id\n        , e.provider_key\n        , e.provider_id\n        , e.encounter_start_date_key\n        , e.encounter_class\n        , coalesce(e.total_claim_cost, 0) as total_cost\n        , coalesce(e.payer_coverage, 0) as payer_coverage\n        , coalesce(e.patient_responsibility, 0) as patient_responsibility\n        , d.date_actual as encounter_date\n        , d.year_actual\n        , coalesce(p.procedure_count, 0) as procedure_count\n        , p.procedure_cost\n    from encounters as e\n    left join dim_date as d on e.encounter_start_date_key = d.date_key\n    left join procedures as p on e.encounter_id = p.encounter_id\n)","final":"final as (\n    select\n        -- surrogate key\n        md5(encounter_id) as cost_analysis_key\n\n        -- encounter reference\n        , encounter_key\n        , encounter_id\n\n        -- dimension keys\n        , patient_key\n        , patient_id\n        , payer_key\n        , payer_id\n        , provider_key\n        , provider_id\n\n        -- date dimensions\n        , encounter_start_date_key as encounter_date_key\n        , encounter_date\n        , year_actual\n\n        -- encounter details\n        , encounter_class\n\n        -- measures: costs\n        , total_cost\n        , payer_coverage\n        , patient_responsibility\n\n        -- measures: percentages\n        , case\n            when total_cost > 0\n            then round(payer_coverage / total_cost * 100, 2)\n            else 0\n        end as coverage_pct\n\n        , case\n            when total_cost > 0\n            then round(patient_responsibility / total_cost * 100, 2)\n            else 0\n        end as patient_cost_pct\n\n        -- measures: procedure costs\n        , procedure_count\n        , case\n            when procedure_count > 0\n            then round(total_cost / procedure_count, 2)\n        end as cost_per_procedure\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from encounters_enriched\n)","procedures":"procedures as (\n    select\n        encounter_id\n        , count(*) as procedure_count\n        , sum(base_cost) as procedure_cost\n    from \"memory\".\"main_staging\".\"stg_synthea__procedures\"\n    group by encounter_id\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='cost_analysis_key',\n        tags=['analytics', 'marts', 'fact']\n    )\n}}\n\n{#\n    Encounter Cost Analysis Fact\n\n    Purpose: Detailed cost breakdown for financial analysis and payer management\n    Grain: One row per encounter (simplified from original spec)\n    Use cases: Financial analysis, payer contract optimization, cost allocation\n\n    Provides cost breakdown including:\n    - Total cost, payer coverage, patient responsibility\n    - Coverage percentages\n    - Cost per procedure\n#}\n\nwith encounters as (\n    select\n        encounter_key\n        , encounter_id\n        , patient_key\n        , patient_id\n        , payer_key\n        , payer_id\n        , provider_key\n        , provider_id\n        , encounter_start_date_key\n        , encounter_class\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , encounter_start_at\n    from {{ ref('fct_encounters') }}\n),\n\ndim_date as (\n    select\n        date_key\n        , date_actual\n        , year_actual\n    from {{ ref('dim_date') }}\n),\n\nprocedures as (\n    select\n        encounter_id\n        , count(*) as procedure_count\n        , sum(base_cost) as procedure_cost\n    from {{ ref('stg_synthea__procedures') }}\n    group by encounter_id\n),\n\n-- join encounters to date and procedures\nencounters_enriched as (\n    select\n        e.encounter_key\n        , e.encounter_id\n        , e.patient_key\n        , e.patient_id\n        , e.payer_key\n        , e.payer_id\n        , e.provider_key\n        , e.provider_id\n        , e.encounter_start_date_key\n        , e.encounter_class\n        , coalesce(e.total_claim_cost, 0) as total_cost\n        , coalesce(e.payer_coverage, 0) as payer_coverage\n        , coalesce(e.patient_responsibility, 0) as patient_responsibility\n        , d.date_actual as encounter_date\n        , d.year_actual\n        , coalesce(p.procedure_count, 0) as procedure_count\n        , p.procedure_cost\n    from encounters as e\n    left join dim_date as d on e.encounter_start_date_key = d.date_key\n    left join procedures as p on e.encounter_id = p.encounter_id\n),\n\nfinal as (\n    select\n        -- surrogate key\n        md5(encounter_id) as cost_analysis_key\n\n        -- encounter reference\n        , encounter_key\n        , encounter_id\n\n        -- dimension keys\n        , patient_key\n        , patient_id\n        , payer_key\n        , payer_id\n        , provider_key\n        , provider_id\n\n        -- date dimensions\n        , encounter_start_date_key as encounter_date_key\n        , encounter_date\n        , year_actual\n\n        -- encounter details\n        , encounter_class\n\n        -- measures: costs\n        , total_cost\n        , payer_coverage\n        , patient_responsibility\n\n        -- measures: percentages\n        , case\n            when total_cost > 0\n            then round(payer_coverage / total_cost * 100, 2)\n            else 0\n        end as coverage_pct\n\n        , case\n            when total_cost > 0\n            then round(patient_responsibility / total_cost * 100, 2)\n            else 0\n        end as patient_cost_pct\n\n        -- measures: procedure costs\n        , procedure_count\n        , case\n            when procedure_count > 0\n            then round(total_cost / procedure_count, 2)\n        end as cost_per_procedure\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from encounters_enriched\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_cost_analysis","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_fct_cost_analysis_cost_analysis_key.2aecf62159"]},"evidence":[{"label":"unique_key","value":"cost_analysis_key"}],"pin_node":"(final select)"},{"check":"join.left-null-propagation","tier":"high","instrument":"both","model_id":"model.healthcare_analytics.fct_cost_analysis","construct":"left_join[encounters_enriched:dim_date]","verdict":{"status":"unknown"},"evidence":[{"label":"left join","value":"encounters_enriched — LEFT JOIN dim_date ON encounters.encounter_start_date_key = dim_date.date_key"},{"label":"unattributable join","value":"encounters_enriched — join key or side binding not statically recoverable"}],"pin_node":"encounters_enriched"},{"check":"join.left-null-propagation","tier":"high","instrument":"both","model_id":"model.healthcare_analytics.fct_cost_analysis","construct":"left_join[encounters_enriched:procedures]","verdict":{"status":"uncovered"},"evidence":[{"label":"left join","value":"encounters_enriched — LEFT JOIN procedures ON encounters.encounter_id = procedures.encounter_id"}],"recommendation":"Add a no-match given: one left-side row whose join key is absent from the right-side given rows, then extend `expect` with that row carrying NULL right-side columns (or the intended fallback). This finding's evidence carries a copy-pasteable given sketch.","pin_node":"encounters_enriched","sketches":["- input: ref('fct_encounters')\n  rows:\n    - {encounter_id: 404}   # 404 has no match below — the no-match path\n- input: ref('stg_synthea__procedures')\n  rows:\n    - {encounter_id: 1}\n# expect: the no-match row with NULL stg_synthea__procedures columns (or the intended fallback)"]}]},{"name":"fct_encounters","path":"models/marts/core/fct_encounters.sql","description":"Encounter fact table containing healthcare visits/encounters. Links to patient, provider, organization, and payer dimensions. Includes date keys, costs, and derived duration.\n","dag":{"nodes":[{"id":"encounters","role":"import"},{"id":"patients","role":"import"},{"id":"providers","role":"import"},{"id":"organizations","role":"import"},{"id":"payers","role":"import"},{"id":"dim_date","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_encounters.sql","role":"final"}],"edges":[{"from":"encounters","to":"final","edge_type":"from"},{"from":"patients","to":"final","edge_type":"left"},{"from":"providers","to":"final","edge_type":"left"},{"from":"organizations","to":"final","edge_type":"left"},{"from":"payers","to":"final","edge_type":"left"},{"from":"dim_date","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","dim_date":"dim_date as (\n    select\n        date_key\n        , date_actual\n    from \"memory\".\"main_marts\".\"dim_date\"\n)","encounters":"encounters as (\n    select * from \"memory\".\"main_staging\".\"stg_synthea__encounters\"\n    \n    \n    where is_dq_valid = true\n    \n\n)","final":"final as (\n    select\n        -- surrogate key\n        row_number() over (order by e.encounter_id) as encounter_key\n\n        -- natural key\n        , e.encounter_id\n\n        -- dimension keys\n        , coalesce(p.patient_key, -1) as patient_key\n        , e.patient_id\n        , coalesce(pr.provider_key, -1) as provider_key\n        , e.provider_id\n        , coalesce(o.organization_key, -1) as organization_key\n        , e.organization_id\n        , coalesce(py.payer_key, -1) as payer_key\n        , e.payer_id\n\n        -- date keys\n        , coalesce(ds.date_key, -1) as encounter_start_date_key\n        , coalesce(de.date_key, -1) as encounter_end_date_key\n\n        -- attributes\n        , e.encounter_class\n        , e.encounter_code\n        , e.encounter_description\n        , e.reason_code\n        , e.reason_description\n\n        -- timestamps\n        , e.encounter_start_at\n        , e.encounter_end_at\n\n        -- derived duration\n        , date_diff('minute', e.encounter_start_at, e.encounter_end_at) as duration_minutes\n\n        -- costs\n        , e.base_encounter_cost\n        , e.total_claim_cost\n        , e.payer_coverage\n        , e.total_claim_cost - coalesce(e.payer_coverage, 0) as patient_responsibility\n\n        -- derived patient context\n        , case\n            when p.birth_date is not null\n            then date_diff('year', p.birth_date, cast(e.encounter_start_at as date))\n        end as patient_age_at_encounter\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from encounters as e\n    left join patients as p on e.patient_id = p.patient_id\n    left join providers as pr on e.provider_id = pr.provider_id\n    left join organizations as o on e.organization_id = o.organization_id\n    left join payers as py on e.payer_id = py.payer_id\n    left join dim_date as ds on cast(e.encounter_start_at as date) = ds.date_actual\n    left join dim_date as de on cast(e.encounter_end_at as date) = de.date_actual\n)","organizations":"organizations as (\n    select\n        organization_key\n        , organization_id\n    from \"memory\".\"main_marts\".\"dim_organizations\"\n)","patients":"patients as (\n    select\n        patient_key\n        , patient_id\n        , birth_date\n    from \"memory\".\"main_marts\".\"dim_patients\"\n    where is_current = true\n)","payers":"payers as (\n    select\n        payer_key\n        , payer_id\n    from \"memory\".\"main_marts\".\"dim_payers\"\n)","providers":"providers as (\n    select\n        provider_key\n        , provider_id\n    from \"memory\".\"main_marts\".\"dim_providers\"\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='encounter_key'\n    )\n}}\n\nwith encounters as (\n    select * from {{ ref('stg_synthea__encounters') }}\n    {{ quarantine_filter() }}\n),\n\npatients as (\n    select\n        patient_key\n        , patient_id\n        , birth_date\n    from {{ ref('dim_patients') }}\n    where is_current = true\n),\n\nproviders as (\n    select\n        provider_key\n        , provider_id\n    from {{ ref('dim_providers') }}\n),\n\norganizations as (\n    select\n        organization_key\n        , organization_id\n    from {{ ref('dim_organizations') }}\n),\n\npayers as (\n    select\n        payer_key\n        , payer_id\n    from {{ ref('dim_payers') }}\n),\n\ndim_date as (\n    select\n        date_key\n        , date_actual\n    from {{ ref('dim_date') }}\n),\n\nfinal as (\n    select\n        -- surrogate key\n        row_number() over (order by e.encounter_id) as encounter_key\n\n        -- natural key\n        , e.encounter_id\n\n        -- dimension keys\n        , coalesce(p.patient_key, -1) as patient_key\n        , e.patient_id\n        , coalesce(pr.provider_key, -1) as provider_key\n        , e.provider_id\n        , coalesce(o.organization_key, -1) as organization_key\n        , e.organization_id\n        , coalesce(py.payer_key, -1) as payer_key\n        , e.payer_id\n\n        -- date keys\n        , coalesce(ds.date_key, -1) as encounter_start_date_key\n        , coalesce(de.date_key, -1) as encounter_end_date_key\n\n        -- attributes\n        , e.encounter_class\n        , e.encounter_code\n        , e.encounter_description\n        , e.reason_code\n        , e.reason_description\n\n        -- timestamps\n        , e.encounter_start_at\n        , e.encounter_end_at\n\n        -- derived duration\n        , date_diff('minute', e.encounter_start_at, e.encounter_end_at) as duration_minutes\n\n        -- costs\n        , e.base_encounter_cost\n        , e.total_claim_cost\n        , e.payer_coverage\n        , e.total_claim_cost - coalesce(e.payer_coverage, 0) as patient_responsibility\n\n        -- derived patient context\n        , case\n            when p.birth_date is not null\n            then date_diff('year', p.birth_date, cast(e.encounter_start_at as date))\n        end as patient_age_at_encounter\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from encounters as e\n    left join patients as p on e.patient_id = p.patient_id\n    left join providers as pr on e.provider_id = pr.provider_id\n    left join organizations as o on e.organization_id = o.organization_id\n    left join payers as py on e.payer_id = py.payer_id\n    left join dim_date as ds on cast(e.encounter_start_at as date) = ds.date_actual\n    left join dim_date as de on cast(e.encounter_end_at as date) = de.date_actual\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_encounters","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_fct_encounters_encounter_key.a3b77e9141"]},"evidence":[{"label":"unique_key","value":"encounter_key"}],"pin_node":"(final select)"}]},{"name":"fct_encounters_incremental","path":"models/marts/core/fct_encounters_incremental.sql","description":"Incremental fact table of encounter events. Appends encounters newer than the latest already-loaded start_time via an is_incremental() filter.","dag":{"nodes":[{"id":"source","role":"import"},{"id":"(final select)","label":"fct_encounters_incremental.sql","role":"final"}],"edges":[{"from":"source","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select\n    encounter_id\n    , patient_id\n    , encounter_type\n    , start_time\n    , total_cost\nfrom source\n\nwhere start_time > (select max(start_time) from \"memory\".\"main_marts\".\"fct_encounters_incremental\")\n","source":"source as (\n    select * from \"memory\".\"main_staging\".\"stg_synthea__encounters\"\n)"},"raw_sql":"{{\n    config(\n        materialized='incremental',\n        unique_key='encounter_id',\n        incremental_strategy='merge',\n        on_schema_change='append_new_columns'\n    )\n}}\n\nwith source as (\n    select * from {{ ref('stg_synthea__encounters') }}\n)\n\nselect\n    encounter_id\n    , patient_id\n    , encounter_type\n    , start_time\n    , total_cost\nfrom source\n{% if is_incremental() %}\nwhere start_time > (select max(start_time) from {{ this }})\n{% endif %}","tests":[{"id":"unit_test.healthcare_analytics.fct_encounters_incremental.test_fct_encounters_incremental_appends_new_encounters","name":"test_fct_encounters_incremental_appends_new_encounters","target_model":"fct_encounters_incremental","changed":false,"description":"fct_encounters_incremental appends encounters newer than the latest loaded start_time. With is_incremental() true only the new encounter is merged; Expected is that single inserted row (the materialization delta), not the resulting table.","tags":[],"meta":{},"defined_in":"models/marts/core/_core__models.yml","is_incremental_mode":true,"overrides":{"macros":{"is_incremental":true}},"given":[{"input":"this","table":{"columns":["encounter_id","encounter_type","patient_id","start_time","total_cost"],"rows":[{"cells":[{"display":"e1","key":{"t":"str","v":"e1"}},{"display":"wellness","key":{"t":"str","v":"wellness"}},{"display":"p1","key":{"t":"str","v":"p1"}},{"display":"2025-01-01 09:00:00","key":{"t":"str","v":"2025-01-01 09:00:00"}},{"display":"100.0","key":{"t":"number","v":"100"}}]}]},"rows":[{"encounter_id":"e1","encounter_type":"wellness","patient_id":"p1","start_time":"2025-01-01 09:00:00","total_cost":100.0}],"format":"dict","is_this":true,"column_meta":{"encounter_id":{"description":"Natural key of the encounter (unique per visit)","tests":[{"name":"not null"},{"name":"unique"}]},"encounter_type":{"description":"Visit class (wellness, emergency, ...)"},"patient_id":{"description":"Patient the encounter belongs to"},"start_time":{"description":"Encounter start timestamp - the incremental high-water mark"},"total_cost":{"description":"Total claim cost for the encounter"}}},{"input":"ref('stg_synthea__encounters')","bound_to_node":"source","table":{"columns":["encounter_id","encounter_type","patient_id","start_time","total_cost"],"rows":[{"cells":[{"display":"e1","key":{"t":"str","v":"e1"}},{"display":"wellness","key":{"t":"str","v":"wellness"}},{"display":"p1","key":{"t":"str","v":"p1"}},{"display":"2025-01-01 09:00:00","key":{"t":"str","v":"2025-01-01 09:00:00"}},{"display":"100.0","key":{"t":"number","v":"100"}}]},{"cells":[{"display":"e2","key":{"t":"str","v":"e2"}},{"display":"emergency","key":{"t":"str","v":"emergency"}},{"display":"p2","key":{"t":"str","v":"p2"}},{"display":"2025-02-01 14:30:00","key":{"t":"str","v":"2025-02-01 14:30:00"}},{"display":"500.0","key":{"t":"number","v":"500"}}]}]},"rows":[{"encounter_id":"e1","encounter_type":"wellness","patient_id":"p1","start_time":"2025-01-01 09:00:00","total_cost":100.0},{"encounter_id":"e2","encounter_type":"emergency","patient_id":"p2","start_time":"2025-02-01 14:30:00","total_cost":500.0}],"format":"dict","column_meta":{"encounter_id":{"description":"Unique encounter identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},"patient_id":{"description":"Foreign key to the patient","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__patients.patient_id"}]}}}],"expected":{"table":{"columns":["encounter_id","encounter_type","patient_id","start_time","total_cost"],"rows":[{"cells":[{"display":"e2","key":{"t":"str","v":"e2"}},{"display":"emergency","key":{"t":"str","v":"emergency"}},{"display":"p2","key":{"t":"str","v":"p2"}},{"display":"2025-02-01 14:30:00","key":{"t":"str","v":"2025-02-01 14:30:00"}},{"display":"500.0","key":{"t":"number","v":"500"}}]}]},"rows":[{"encounter_id":"e2","encounter_type":"emergency","patient_id":"p2","start_time":"2025-02-01 14:30:00","total_cost":500.0}],"format":"dict","column_meta":{"encounter_id":{"description":"Natural key of the encounter (unique per visit)","tests":[{"name":"not null"},{"name":"unique"}]},"encounter_type":{"description":"Visit class (wellness, emergency, ...)"},"patient_id":{"description":"Patient the encounter belongs to"},"start_time":{"description":"Encounter start timestamp - the incremental high-water mark"},"total_cost":{"description":"Total claim cost for the encounter"}}}}],"is_recursive":false,"is_incremental":true,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_encounters_incremental","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_fct_encounters_incremental_encounter_id.a165c01d01"]},"evidence":[{"label":"unique_key","value":"encounter_id"}],"pin_node":"(final select)"},{"check":"incremental.branch-coverage","tier":"high","instrument":"unit-test","model_id":"model.healthcare_analytics.fct_encounters_incremental","construct":"config.materialized","verdict":{"status":"uncovered"},"evidence":[{"label":"materialized","value":"incremental (strategy: merge)"},{"label":"branch coverage","value":"true-only — 1 test(s) override is_incremental to true; none exercise the initial full-build (false) branch"},{"label":"missing branch","value":"the initial full-build branch (is_incremental() = false) runs in no unit test"}],"recommendation":"Add a unit test for each missing is_incremental() branch: one with `overrides: macros: is_incremental: true` (mock the prior model state with a `given: - input: this` entry) to exercise the incremental branch, and one without the override for the initial full build (dbt compiles is_incremental() as false by default). This finding's evidence carries a copy-pasteable unit-test sketch per missing branch.","pin_node":"(final select)","sketches":["- name: test_fct_encounters_incremental_initial_build\n  model: fct_encounters_incremental\n  # no overrides block — dbt compiles is_incremental() as false by default\n  given:\n    - input: ref('...')\n      rows:\n        - {...}\n  # expect: the full first-build output"]}]},{"name":"fct_encounters_monthly","path":"models/marts/core/fct_encounters_monthly.sql","description":"Monthly aggregated encounter statistics by encounter class. Provides counts, costs, and patient metrics grouped by year-month and encounter type.\n","dag":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"encounters_with_date","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_encounters_monthly.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_with_date","edge_type":"from"},{"from":"dim_date","to":"encounters_with_date","edge_type":"inner"},{"from":"encounters_with_date","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","dim_date":"dim_date as (\n    select\n        date_key\n        , year_actual\n        , month_actual\n    from \"memory\".\"main_marts\".\"dim_date\"\n)","encounters":"encounters as (\n    select\n        encounter_id\n        , patient_id\n        , encounter_start_date_key\n        , encounter_class\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , duration_minutes\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n)","encounters_with_date":"encounters_with_date as (\n    select\n        e.*\n        , d.year_actual\n        , d.month_actual\n        , cast(d.year_actual as varchar) || '-' ||\n            lpad(cast(d.month_actual as varchar), 2, '0') as year_month\n    from encounters e\n    inner join dim_date d on e.encounter_start_date_key = d.date_key\n    where e.encounter_start_date_key != -1\n)","final":"final as (\n    select\n        year_month\n        , year_actual\n        , month_actual\n        , encounter_class\n        , count(*) as encounter_count\n        , count(distinct patient_id) as unique_patients\n        , sum(total_claim_cost) as total_claim_cost\n        , sum(payer_coverage) as total_payer_coverage\n        , sum(patient_responsibility) as total_patient_responsibility\n        , avg(duration_minutes) as avg_duration_minutes\n        , current_timestamp as _loaded_at\n    from encounters_with_date\n    group by year_month, year_actual, month_actual, encounter_class\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key=['year_month', 'encounter_class']\n    )\n}}\n\nwith encounters as (\n    select\n        encounter_id\n        , patient_id\n        , encounter_start_date_key\n        , encounter_class\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , duration_minutes\n    from {{ ref('fct_encounters') }}\n),\n\ndim_date as (\n    select\n        date_key\n        , year_actual\n        , month_actual\n    from {{ ref('dim_date') }}\n),\n\nencounters_with_date as (\n    select\n        e.*\n        , d.year_actual\n        , d.month_actual\n        , cast(d.year_actual as varchar) || '-' ||\n            lpad(cast(d.month_actual as varchar), 2, '0') as year_month\n    from encounters e\n    inner join dim_date d on e.encounter_start_date_key = d.date_key\n    where e.encounter_start_date_key != -1\n),\n\nfinal as (\n    select\n        year_month\n        , year_actual\n        , month_actual\n        , encounter_class\n        , count(*) as encounter_count\n        , count(distinct patient_id) as unique_patients\n        , sum(total_claim_cost) as total_claim_cost\n        , sum(payer_coverage) as total_payer_coverage\n        , sum(patient_responsibility) as total_patient_responsibility\n        , avg(duration_minutes) as avg_duration_minutes\n        , current_timestamp as _loaded_at\n    from encounters_with_date\n    group by year_month, year_actual, month_actual, encounter_class\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_encounters_monthly","construct":"config.unique_key","verdict":{"status":"uncovered"},"evidence":[{"label":"unique_key","value":"year_month, encounter_class"}],"recommendation":"Add a uniqueness data test at the declared grain: `unique` on a single-column key, or `dbt_utils.unique_combination_of_columns` over the composite key columns.","pin_node":"(final select)"}]},{"name":"fct_encounters_yearly","path":"models/marts/core/fct_encounters_yearly.sql","description":"Yearly aggregated encounter statistics by encounter class. Provides counts, costs, patient metrics, and encounters per patient ratio.\n","dag":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"encounters_with_date","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_encounters_yearly.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_with_date","edge_type":"from"},{"from":"dim_date","to":"encounters_with_date","edge_type":"inner"},{"from":"encounters_with_date","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","dim_date":"dim_date as (\n    select\n        date_key\n        , year_actual\n    from \"memory\".\"main_marts\".\"dim_date\"\n)","encounters":"encounters as (\n    select\n        encounter_id\n        , patient_id\n        , encounter_start_date_key\n        , encounter_class\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , duration_minutes\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n)","encounters_with_date":"encounters_with_date as (\n    select\n        e.*\n        , d.year_actual\n    from encounters e\n    inner join dim_date d on e.encounter_start_date_key = d.date_key\n    where e.encounter_start_date_key != -1\n)","final":"final as (\n    select\n        year_actual\n        , encounter_class\n        , count(*) as encounter_count\n        , count(distinct patient_id) as unique_patients\n        , sum(total_claim_cost) as total_claim_cost\n        , sum(payer_coverage) as total_payer_coverage\n        , sum(patient_responsibility) as total_patient_responsibility\n        , avg(duration_minutes) as avg_duration_minutes\n        , cast(count(*) as decimal(18, 2)) / nullif(count(distinct patient_id), 0) as encounters_per_patient\n        , current_timestamp as _loaded_at\n    from encounters_with_date\n    group by year_actual, encounter_class\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key=['year_actual', 'encounter_class']\n    )\n}}\n\nwith encounters as (\n    select\n        encounter_id\n        , patient_id\n        , encounter_start_date_key\n        , encounter_class\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , duration_minutes\n    from {{ ref('fct_encounters') }}\n),\n\ndim_date as (\n    select\n        date_key\n        , year_actual\n    from {{ ref('dim_date') }}\n),\n\nencounters_with_date as (\n    select\n        e.*\n        , d.year_actual\n    from encounters e\n    inner join dim_date d on e.encounter_start_date_key = d.date_key\n    where e.encounter_start_date_key != -1\n),\n\nfinal as (\n    select\n        year_actual\n        , encounter_class\n        , count(*) as encounter_count\n        , count(distinct patient_id) as unique_patients\n        , sum(total_claim_cost) as total_claim_cost\n        , sum(payer_coverage) as total_payer_coverage\n        , sum(patient_responsibility) as total_patient_responsibility\n        , avg(duration_minutes) as avg_duration_minutes\n        , cast(count(*) as decimal(18, 2)) / nullif(count(distinct patient_id), 0) as encounters_per_patient\n        , current_timestamp as _loaded_at\n    from encounters_with_date\n    group by year_actual, encounter_class\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_encounters_yearly","construct":"config.unique_key","verdict":{"status":"uncovered"},"evidence":[{"label":"unique_key","value":"year_actual, encounter_class"}],"recommendation":"Add a uniqueness data test at the declared grain: `unique` on a single-column key, or `dbt_utils.unique_combination_of_columns` over the composite key columns.","pin_node":"(final select)"}]},{"name":"fct_patient_summary","path":"models/marts/analytics/fct_patient_summary.sql","description":"Annual patient-level aggregations for outcomes tracking and population health analysis.\nOne row per patient per calendar year with comprehensive utilization and cost metrics.\nGrain: (patient_id, year_actual)\n\nUse cases:\n- Patient outcomes tracking over time\n- Annual cost summaries and trends\n- Cohort analysis and patient stratification\n- Health trajectory visualization\n- High-cost patient identification\n","dag":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"procedures","role":"import"},{"id":"conditions","role":"import"},{"id":"encounters_with_year","role":"transform"},{"id":"conditions_per_patient_year","role":"transform"},{"id":"patient_year_agg","role":"transform"},{"id":"with_conditions","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_patient_summary.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_with_year","edge_type":"from"},{"from":"dim_date","to":"encounters_with_year","edge_type":"inner"},{"from":"procedures","to":"encounters_with_year","edge_type":"left"},{"from":"conditions","to":"conditions_per_patient_year","edge_type":"from"},{"from":"encounters_with_year","to":"patient_year_agg","edge_type":"from"},{"from":"patient_year_agg","to":"with_conditions","edge_type":"from"},{"from":"conditions_per_patient_year","to":"with_conditions","edge_type":"left"},{"from":"with_conditions","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","conditions":"conditions as (\n    select\n        patient_id\n        , condition_code\n        , extract(year from condition_start_date) as condition_year\n    from \"memory\".\"main_staging\".\"stg_synthea__conditions\"\n)","conditions_per_patient_year":"conditions_per_patient_year as (\n    select\n        patient_id\n        , condition_year as year_actual\n        , count(distinct condition_code) as condition_count\n    from conditions\n    group by patient_id, condition_year\n)","dim_date":"dim_date as (\n    select\n        date_key\n        , year_actual\n    from \"memory\".\"main_marts\".\"dim_date\"\n)","encounters":"encounters as (\n    select\n        encounter_key\n        , encounter_id\n        , patient_key\n        , patient_id\n        , provider_key\n        , provider_id\n        , organization_key\n        , organization_id\n        , payer_key\n        , payer_id\n        , encounter_start_date_key\n        , encounter_class\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , patient_age_at_encounter\n        , encounter_start_at\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n    where patient_key != -1\n)","encounters_with_year":"encounters_with_year as (\n    select\n        e.*\n        , d.year_actual\n        , coalesce(pr.procedure_count, 0) as procedure_count\n    from encounters as e\n    inner join dim_date as d on e.encounter_start_date_key = d.date_key\n    left join procedures as pr on e.encounter_id = pr.encounter_id\n    where e.encounter_start_date_key != -1\n)","final":"final as (\n    select\n        -- surrogate key\n        md5(cast(patient_id as varchar) || '-' || cast(year_actual as varchar)) as patient_summary_key\n\n        -- dimension keys\n        , patient_key\n        , patient_id\n\n        -- time grain\n        , year_actual\n\n        -- patient context\n        , patient_age_at_year_end\n\n        -- measures: counts\n        , encounter_count\n        , procedure_count\n        , condition_count\n        , unique_providers\n        , unique_organizations\n\n        -- measures: costs\n        , coalesce(total_cost, 0) as total_cost\n        , coalesce(payer_coverage, 0) as payer_coverage\n        , coalesce(patient_responsibility, 0) as patient_responsibility\n\n        -- measures: ratios\n        , case\n            when total_cost > 0\n            then round(payer_coverage / total_cost * 100, 2)\n        end as payer_coverage_pct\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from with_conditions\n)","patient_year_agg":"patient_year_agg as (\n    select\n        e.patient_id\n        , e.year_actual\n        , max(e.patient_key) as patient_key\n        , count(*) as encounter_count\n        , sum(e.procedure_count) as procedure_count\n        , sum(e.total_claim_cost) as total_cost\n        , sum(e.payer_coverage) as payer_coverage\n        , sum(e.patient_responsibility) as patient_responsibility\n        , count(distinct e.provider_id) as unique_providers\n        , count(distinct e.organization_id) as unique_organizations\n        , max(e.patient_age_at_encounter) as patient_age_at_year_end\n    from encounters_with_year as e\n    group by e.patient_id, e.year_actual\n)","procedures":"procedures as (\n    select\n        encounter_id\n        , count(*) as procedure_count\n    from \"memory\".\"main_staging\".\"stg_synthea__procedures\"\n    group by encounter_id\n)","with_conditions":"with_conditions as (\n    select\n        pya.*\n        , coalesce(c.condition_count, 0) as condition_count\n    from patient_year_agg as pya\n    left join conditions_per_patient_year as c\n        on pya.patient_id = c.patient_id\n        and pya.year_actual = c.year_actual\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='patient_summary_key',\n        tags=['analytics', 'marts', 'fact']\n    )\n}}\n\n{#\n    Annual Patient Summary Fact\n\n    Purpose: Patient-level annual snapshots for outcomes tracking\n    Grain: One row per patient per calendar year\n    Use cases: Patient outcomes, annual cost summaries, cohort analysis\n\n    Aggregates encounters, procedures, conditions, and costs by patient and year.\n    Joins to dimensions for foreign key lookups.\n#}\n\nwith encounters as (\n    select\n        encounter_key\n        , encounter_id\n        , patient_key\n        , patient_id\n        , provider_key\n        , provider_id\n        , organization_key\n        , organization_id\n        , payer_key\n        , payer_id\n        , encounter_start_date_key\n        , encounter_class\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , patient_age_at_encounter\n        , encounter_start_at\n    from {{ ref('fct_encounters') }}\n    where patient_key != -1\n),\n\ndim_date as (\n    select\n        date_key\n        , year_actual\n    from {{ ref('dim_date') }}\n),\n\nprocedures as (\n    select\n        encounter_id\n        , count(*) as procedure_count\n    from {{ ref('stg_synthea__procedures') }}\n    group by encounter_id\n),\n\nconditions as (\n    select\n        patient_id\n        , condition_code\n        , extract(year from condition_start_date) as condition_year\n    from {{ ref('stg_synthea__conditions') }}\n),\n\n-- join encounters to date dimension to get year\nencounters_with_year as (\n    select\n        e.*\n        , d.year_actual\n        , coalesce(pr.procedure_count, 0) as procedure_count\n    from encounters as e\n    inner join dim_date as d on e.encounter_start_date_key = d.date_key\n    left join procedures as pr on e.encounter_id = pr.encounter_id\n    where e.encounter_start_date_key != -1\n),\n\n-- count distinct conditions per patient per year\nconditions_per_patient_year as (\n    select\n        patient_id\n        , condition_year as year_actual\n        , count(distinct condition_code) as condition_count\n    from conditions\n    group by patient_id, condition_year\n),\n\n-- aggregate by patient and year\npatient_year_agg as (\n    select\n        e.patient_id\n        , e.year_actual\n        , max(e.patient_key) as patient_key\n        , count(*) as encounter_count\n        , sum(e.procedure_count) as procedure_count\n        , sum(e.total_claim_cost) as total_cost\n        , sum(e.payer_coverage) as payer_coverage\n        , sum(e.patient_responsibility) as patient_responsibility\n        , count(distinct e.provider_id) as unique_providers\n        , count(distinct e.organization_id) as unique_organizations\n        , max(e.patient_age_at_encounter) as patient_age_at_year_end\n    from encounters_with_year as e\n    group by e.patient_id, e.year_actual\n),\n\n-- join condition counts\nwith_conditions as (\n    select\n        pya.*\n        , coalesce(c.condition_count, 0) as condition_count\n    from patient_year_agg as pya\n    left join conditions_per_patient_year as c\n        on pya.patient_id = c.patient_id\n        and pya.year_actual = c.year_actual\n),\n\nfinal as (\n    select\n        -- surrogate key\n        md5(cast(patient_id as varchar) || '-' || cast(year_actual as varchar)) as patient_summary_key\n\n        -- dimension keys\n        , patient_key\n        , patient_id\n\n        -- time grain\n        , year_actual\n\n        -- patient context\n        , patient_age_at_year_end\n\n        -- measures: counts\n        , encounter_count\n        , procedure_count\n        , condition_count\n        , unique_providers\n        , unique_organizations\n\n        -- measures: costs\n        , coalesce(total_cost, 0) as total_cost\n        , coalesce(payer_coverage, 0) as payer_coverage\n        , coalesce(patient_responsibility, 0) as patient_responsibility\n\n        -- measures: ratios\n        , case\n            when total_cost > 0\n            then round(payer_coverage / total_cost * 100, 2)\n        end as payer_coverage_pct\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from with_conditions\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_patient_summary","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_fct_patient_summary_patient_summary_key.e532e1ff45"]},"evidence":[{"label":"unique_key","value":"patient_summary_key"}],"pin_node":"(final select)"}]},{"name":"fct_provider_metrics","path":"models/marts/analytics/fct_provider_metrics.sql","description":"Monthly provider-level utilization and performance metrics.\nOne row per provider per calendar month with patient volumes, costs, and efficiency metrics.\nGrain: (provider_id, year_actual, month_actual)\n\nUse cases:\n- Provider performance tracking\n- Workload distribution analysis\n- Cost efficiency comparisons\n- Capacity planning and staffing\n- Quality improvement initiatives\n","dag":{"nodes":[{"id":"encounters","role":"import"},{"id":"dim_date","role":"import"},{"id":"procedures","role":"import"},{"id":"encounters_with_date","role":"transform"},{"id":"provider_month_agg","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"fct_provider_metrics.sql","role":"final"}],"edges":[{"from":"encounters","to":"encounters_with_date","edge_type":"from"},{"from":"dim_date","to":"encounters_with_date","edge_type":"inner"},{"from":"procedures","to":"encounters_with_date","edge_type":"left"},{"from":"encounters_with_date","to":"provider_month_agg","edge_type":"from"},{"from":"provider_month_agg","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","dim_date":"dim_date as (\n    select\n        date_key\n        , year_actual\n        , month_actual\n    from \"memory\".\"main_marts\".\"dim_date\"\n)","encounters":"encounters as (\n    select\n        encounter_key\n        , encounter_id\n        , patient_key\n        , patient_id\n        , provider_key\n        , provider_id\n        , organization_key\n        , organization_id\n        , encounter_start_date_key\n        , total_claim_cost\n        , payer_coverage\n        , duration_minutes\n        , patient_age_at_encounter\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n    where provider_key != -1\n)","encounters_with_date":"encounters_with_date as (\n    select\n        e.*\n        , d.year_actual\n        , d.month_actual\n        , cast(d.year_actual as varchar)\n            || '-'\n            || lpad(cast(d.month_actual as varchar), 2, '0') as year_month_str\n        , coalesce(pr.procedure_count, 0) as procedure_count\n    from encounters as e\n    inner join dim_date as d on e.encounter_start_date_key = d.date_key\n    left join procedures as pr on e.encounter_id = pr.encounter_id\n    where e.encounter_start_date_key != -1\n)","final":"final as (\n    select\n        -- surrogate key\n        md5(cast(provider_id as varchar) || '-' || year_month_str) as provider_metrics_key\n\n        -- dimension keys\n        , provider_key\n        , provider_id\n        , organization_key\n        , organization_id\n\n        -- time grain\n        , year_actual\n        , month_actual\n        , year_month_str\n\n        -- measures: counts\n        , encounter_count\n        , unique_patient_count\n        , total_procedures\n\n        -- measures: averages\n        , round(avg_patient_age, 2) as avg_patient_age\n        , round(avg_encounter_duration_minutes, 2) as avg_encounter_duration_minutes\n\n        -- measures: costs\n        , coalesce(total_cost, 0) as total_cost\n        , coalesce(total_payer_coverage, 0) as total_payer_coverage\n\n        -- measures: derived ratios\n        , case\n            when encounter_count > 0\n            then round(total_cost / encounter_count, 2)\n            else 0\n        end as avg_cost_per_encounter\n\n        , case\n            when unique_patient_count > 0\n            then round(cast(encounter_count as decimal) / unique_patient_count, 2)\n            else 0\n        end as encounters_per_patient_avg\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from provider_month_agg\n)","procedures":"procedures as (\n    select\n        encounter_id\n        , count(*) as procedure_count\n    from \"memory\".\"main_staging\".\"stg_synthea__procedures\"\n    group by encounter_id\n)","provider_month_agg":"provider_month_agg as (\n    select\n        e.provider_id\n        , e.provider_key\n        , e.organization_id\n        , e.organization_key\n        , e.year_actual\n        , e.month_actual\n        , e.year_month_str\n\n        -- counts\n        , count(*) as encounter_count\n        , count(distinct e.patient_id) as unique_patient_count\n\n        -- patient metrics\n        , avg(e.patient_age_at_encounter) as avg_patient_age\n\n        -- encounter metrics\n        , avg(e.duration_minutes) as avg_encounter_duration_minutes\n\n        -- procedure metrics\n        , sum(e.procedure_count) as total_procedures\n\n        -- cost metrics\n        , sum(e.total_claim_cost) as total_cost\n        , sum(e.payer_coverage) as total_payer_coverage\n\n    from encounters_with_date as e\n    group by\n        e.provider_id\n        , e.provider_key\n        , e.organization_id\n        , e.organization_key\n        , e.year_actual\n        , e.month_actual\n        , e.year_month_str\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        unique_key='provider_metrics_key',\n        tags=['analytics', 'marts', 'fact']\n    )\n}}\n\n{#\n    Monthly Provider Metrics Fact\n\n    Purpose: Provider-level utilization and performance metrics\n    Grain: One row per provider per calendar month\n    Use cases: Provider performance dashboards, utilization trending, quality measures\n\n    Aggregates encounters, patients, procedures, and costs by provider and month.\n    Calculates derived metrics like avg cost per encounter and encounters per patient.\n#}\n\nwith encounters as (\n    select\n        encounter_key\n        , encounter_id\n        , patient_key\n        , patient_id\n        , provider_key\n        , provider_id\n        , organization_key\n        , organization_id\n        , encounter_start_date_key\n        , total_claim_cost\n        , payer_coverage\n        , duration_minutes\n        , patient_age_at_encounter\n    from {{ ref('fct_encounters') }}\n    where provider_key != -1\n),\n\ndim_date as (\n    select\n        date_key\n        , year_actual\n        , month_actual\n    from {{ ref('dim_date') }}\n),\n\nprocedures as (\n    select\n        encounter_id\n        , count(*) as procedure_count\n    from {{ ref('stg_synthea__procedures') }}\n    group by encounter_id\n),\n\n-- join encounters to date dimension to get year/month\nencounters_with_date as (\n    select\n        e.*\n        , d.year_actual\n        , d.month_actual\n        , cast(d.year_actual as varchar)\n            || '-'\n            || lpad(cast(d.month_actual as varchar), 2, '0') as year_month_str\n        , coalesce(pr.procedure_count, 0) as procedure_count\n    from encounters as e\n    inner join dim_date as d on e.encounter_start_date_key = d.date_key\n    left join procedures as pr on e.encounter_id = pr.encounter_id\n    where e.encounter_start_date_key != -1\n),\n\n-- aggregate by provider and year-month\nprovider_month_agg as (\n    select\n        e.provider_id\n        , e.provider_key\n        , e.organization_id\n        , e.organization_key\n        , e.year_actual\n        , e.month_actual\n        , e.year_month_str\n\n        -- counts\n        , count(*) as encounter_count\n        , count(distinct e.patient_id) as unique_patient_count\n\n        -- patient metrics\n        , avg(e.patient_age_at_encounter) as avg_patient_age\n\n        -- encounter metrics\n        , avg(e.duration_minutes) as avg_encounter_duration_minutes\n\n        -- procedure metrics\n        , sum(e.procedure_count) as total_procedures\n\n        -- cost metrics\n        , sum(e.total_claim_cost) as total_cost\n        , sum(e.payer_coverage) as total_payer_coverage\n\n    from encounters_with_date as e\n    group by\n        e.provider_id\n        , e.provider_key\n        , e.organization_id\n        , e.organization_key\n        , e.year_actual\n        , e.month_actual\n        , e.year_month_str\n),\n\nfinal as (\n    select\n        -- surrogate key\n        md5(cast(provider_id as varchar) || '-' || year_month_str) as provider_metrics_key\n\n        -- dimension keys\n        , provider_key\n        , provider_id\n        , organization_key\n        , organization_id\n\n        -- time grain\n        , year_actual\n        , month_actual\n        , year_month_str\n\n        -- measures: counts\n        , encounter_count\n        , unique_patient_count\n        , total_procedures\n\n        -- measures: averages\n        , round(avg_patient_age, 2) as avg_patient_age\n        , round(avg_encounter_duration_minutes, 2) as avg_encounter_duration_minutes\n\n        -- measures: costs\n        , coalesce(total_cost, 0) as total_cost\n        , coalesce(total_payer_coverage, 0) as total_payer_coverage\n\n        -- measures: derived ratios\n        , case\n            when encounter_count > 0\n            then round(total_cost / encounter_count, 2)\n            else 0\n        end as avg_cost_per_encounter\n\n        , case\n            when unique_patient_count > 0\n            then round(cast(encounter_count as decimal) / unique_patient_count, 2)\n            else 0\n        end as encounters_per_patient_avg\n\n        -- metadata\n        , current_timestamp as _loaded_at\n\n    from provider_month_agg\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.fct_provider_metrics","construct":"config.unique_key","verdict":{"status":"covered","by":["test.healthcare_analytics.unique_fct_provider_metrics_provider_metrics_key.d58939d602"]},"evidence":[{"label":"unique_key","value":"provider_metrics_key"}],"pin_node":"(final select)"}]},{"name":"int_dq_quarantine__encounters","path":"models/intermediate/quarantine/int_dq_quarantine__encounters.sql","description":"Encounters that failed data quality validations and are excluded from downstream marts.\n\nRecords are quarantined when any of the following validations fail:\n- valid_encounter_timestamps: encounter_end_at >= encounter_start_at\n- no_future_encounter_dates: encounter_start_at <= current_timestamp\n- end_after_1900: encounter_end_at >= timestamp '1900-01-01'\n- start_after_1900: encounter_start_at >= timestamp '1900-01-01'\n\nThis table preserves data quality violations for investigation without polluting fact tables.\n","dag":{"nodes":[],"edges":[]},"compiled_sql":{"int_dq_quarantine__encounters":"\n\n\n\n-- Encounters quarantined due to data quality violations\n\nselect * from \"memory\".\"main_staging\".\"stg_synthea__encounters\"\nwhere is_dq_valid = false\n\n\n-- cute-dbt fixture: synthetic body mod"},"raw_sql":"{{\n    config(\n        materialized='table',\n        tags=['intermediate', 'quarantine', 'data_quality']\n    )\n}}\n\n{{ generate_quarantine_model(\n    source_model='stg_synthea__encounters',\n    description='Encounters quarantined due to data quality violations'\n) }}\n\n-- cute-dbt fixture: synthetic body mod","tests":[],"is_recursive":false},{"name":"int_dq_quarantine__medications","path":"models/intermediate/quarantine/int_dq_quarantine__medications.sql","description":"Medications that failed data quality validations and are excluded from downstream marts.\n\nRecords are quarantined when any of the following validations fail:\n- valid_medication_dates: medication_end_at is null or medication_end_at >= medication_start_at\n- no_future_medication_dates: cast(medication_start_at as date) <= current_date\n- start_after_1900: medication_start_at >= timestamp '1900-01-01'\n- end_after_1900_if_present: medication_end_at is null or medication_end_at >= timestamp '1900-01-01'\n\nThis table preserves data quality violations for investigation without polluting fact tables.\n","dag":{"nodes":[],"edges":[]},"compiled_sql":{"int_dq_quarantine__medications":"\n\n\n\n-- Medications quarantined due to data quality violations\n\nselect * from \"memory\".\"main_staging\".\"stg_synthea__medications\"\nwhere is_dq_valid = false\n"},"raw_sql":"{{\n    config(\n        materialized='table',\n        tags=['intermediate', 'quarantine', 'data_quality']\n    )\n}}\n\n{{ generate_quarantine_model(\n    source_model='stg_synthea__medications',\n    description='Medications quarantined due to data quality violations'\n) }}","tests":[],"is_recursive":false},{"name":"int_encounters__enriched","path":"models/intermediate/healthcare/int_encounters__enriched.sql","description":"Enriched encounter model that aggregates clinical event counts and costs per encounter. Joins conditions, medications, and procedures to provide a complete view of each encounter's clinical activity and associated costs.\n","dag":{"nodes":[{"id":"encounters","role":"import"},{"id":"conditions","role":"import"},{"id":"medications","role":"import"},{"id":"procedures","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"int_encounters__enriched.sql","role":"final"}],"edges":[{"from":"encounters","to":"final","edge_type":"from"},{"from":"conditions","to":"final","edge_type":"left"},{"from":"medications","to":"final","edge_type":"left"},{"from":"procedures","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","conditions":"conditions as (\n    select\n        encounter_id\n        , count(*) as condition_count\n        , cast(0 as decimal(18, 2)) as total_condition_cost\n    from \"memory\".\"main_staging\".\"stg_synthea__conditions\"\n    group by encounter_id\n)","encounters":"encounters as (\n    select\n        encounter_id\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n)","final":"final as (\n    select\n        e.encounter_id\n        , coalesce(c.condition_count, 0) as condition_count\n        , coalesce(m.medication_count, 0) as medication_count\n        , coalesce(p.procedure_count, 0) as procedure_count\n        , coalesce(c.condition_count, 0)\n            + coalesce(m.medication_count, 0)\n            + coalesce(p.procedure_count, 0) as total_event_count\n        , coalesce(c.total_condition_cost, 0) as total_condition_cost\n        , coalesce(m.total_medication_cost, 0) as total_medication_cost\n        , coalesce(p.total_procedure_cost, 0) as total_procedure_cost\n        , coalesce(c.total_condition_cost, 0)\n            + coalesce(m.total_medication_cost, 0)\n            + coalesce(p.total_procedure_cost, 0) as total_event_cost\n    from encounters as e\n    left join conditions as c on e.encounter_id = c.encounter_id\n    left join medications as m on e.encounter_id = m.encounter_id\n    left join procedures as p on e.encounter_id = p.encounter_id\n)","medications":"medications as (\n    select\n        encounter_id\n        , count(*) as medication_count\n        , coalesce(sum(total_cost), 0) as total_medication_cost\n    from \"memory\".\"main_staging\".\"stg_synthea__medications\"\n    \n    \n    where is_dq_valid = true\n    \n\n    group by encounter_id\n)","procedures":"procedures as (\n    select\n        encounter_id\n        , count(*) as procedure_count\n        , coalesce(sum(base_cost), 0) as total_procedure_cost\n    from \"memory\".\"main_staging\".\"stg_synthea__procedures\"\n    group by encounter_id\n)"},"raw_sql":"{{\n    config(\n        materialized='view'\n    )\n}}\n\nwith encounters as (\n    select\n        encounter_id\n    from {{ ref('fct_encounters') }}\n),\n\nconditions as (\n    select\n        encounter_id\n        , count(*) as condition_count\n        , cast(0 as decimal(18, 2)) as total_condition_cost\n    from {{ ref('stg_synthea__conditions') }}\n    group by encounter_id\n),\n\nmedications as (\n    select\n        encounter_id\n        , count(*) as medication_count\n        , coalesce(sum(total_cost), 0) as total_medication_cost\n    from {{ ref('stg_synthea__medications') }}\n    {{ quarantine_filter() }}\n    group by encounter_id\n),\n\nprocedures as (\n    select\n        encounter_id\n        , count(*) as procedure_count\n        , coalesce(sum(base_cost), 0) as total_procedure_cost\n    from {{ ref('stg_synthea__procedures') }}\n    group by encounter_id\n),\n\nfinal as (\n    select\n        e.encounter_id\n        , coalesce(c.condition_count, 0) as condition_count\n        , coalesce(m.medication_count, 0) as medication_count\n        , coalesce(p.procedure_count, 0) as procedure_count\n        , coalesce(c.condition_count, 0)\n            + coalesce(m.medication_count, 0)\n            + coalesce(p.procedure_count, 0) as total_event_count\n        , coalesce(c.total_condition_cost, 0) as total_condition_cost\n        , coalesce(m.total_medication_cost, 0) as total_medication_cost\n        , coalesce(p.total_procedure_cost, 0) as total_procedure_cost\n        , coalesce(c.total_condition_cost, 0)\n            + coalesce(m.total_medication_cost, 0)\n            + coalesce(p.total_procedure_cost, 0) as total_event_cost\n    from encounters as e\n    left join conditions as c on e.encounter_id = c.encounter_id\n    left join medications as m on e.encounter_id = m.encounter_id\n    left join procedures as p on e.encounter_id = p.encounter_id\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"int_patients__with_conditions","path":"models/intermediate/healthcare/int_patients__with_conditions.sql","description":"Patient-level condition history with aggregated statistics and chronic disease flags. Provides counts of total and active conditions, condition date ranges, and boolean flags for common chronic conditions (diabetes, hypertension, heart disease).\nIMPORTANT: Chronic condition flags use simplified text matching on condition descriptions. This is for analytics/reporting only, not clinical decisions.\n","dag":{"nodes":[{"id":"patients","role":"import"},{"id":"conditions","role":"import"},{"id":"condition_stats","role":"transform"},{"id":"chronic_flags","role":"transform"},{"id":"chronic_count","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"int_patients__with_conditions.sql","role":"final"}],"edges":[{"from":"conditions","to":"condition_stats","edge_type":"from"},{"from":"conditions","to":"chronic_flags","edge_type":"from"},{"from":"chronic_flags","to":"chronic_count","edge_type":"from"},{"from":"patients","to":"final","edge_type":"from"},{"from":"condition_stats","to":"final","edge_type":"left"},{"from":"chronic_flags","to":"final","edge_type":"left"},{"from":"chronic_count","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","chronic_count":"chronic_count as (\n    select\n        patient_id\n        , has_diabetes + has_hypertension + has_heart_disease as chronic_condition_count\n    from chronic_flags\n)","chronic_flags":"chronic_flags as (\n    select\n        patient_id\n        , max(case\n            when lower(condition_description) like '%diabetes%' then 1\n            else 0\n        end) as has_diabetes\n        , max(case\n            when lower(condition_description) like '%hypertension%'\n                or lower(condition_description) like '%high blood pressure%' then 1\n            else 0\n        end) as has_hypertension\n        , max(case\n            when lower(condition_description) like '%heart disease%'\n                or lower(condition_description) like '%cardiac%'\n                or lower(condition_description) like '%coronary%'\n                or lower(condition_description) like '%atrial fibrillation%' then 1\n            else 0\n        end) as has_heart_disease\n    from conditions\n    group by patient_id\n)","condition_stats":"condition_stats as (\n    select\n        patient_id\n        , count(*) as total_conditions\n        , sum(case when condition_end_date is null then 1 else 0 end) as active_conditions\n        , min(condition_start_date) as first_condition_date\n        , max(condition_start_date) as last_condition_date\n    from conditions\n    group by patient_id\n)","conditions":"conditions as (\n    select\n        patient_id\n        , condition_start_date\n        , condition_end_date\n        , condition_code\n        , condition_description\n    from \"memory\".\"main_staging\".\"stg_synthea__conditions\"\n)","final":"final as (\n    select\n        p.patient_id\n        , coalesce(cs.total_conditions, 0) as total_conditions\n        , coalesce(cs.active_conditions, 0) as active_conditions\n        , cs.first_condition_date\n        , cs.last_condition_date\n        , coalesce(cast(cf.has_diabetes as boolean), false) as has_diabetes\n        , coalesce(cast(cf.has_hypertension as boolean), false) as has_hypertension\n        , coalesce(cast(cf.has_heart_disease as boolean), false) as has_heart_disease\n        , coalesce(cc.chronic_condition_count, 0) as chronic_condition_count\n    from patients p\n    left join condition_stats cs on p.patient_id = cs.patient_id\n    left join chronic_flags cf on p.patient_id = cf.patient_id\n    left join chronic_count cc on p.patient_id = cc.patient_id\n)","patients":"patients as (\n    select\n        patient_id\n    from \"memory\".\"main_marts\".\"dim_patients\"\n    where is_current = true\n)"},"raw_sql":"{{\n    config(\n        materialized='view'\n    )\n}}\n\n{#\n    Patient condition history with chronic disease flags.\n\n    IMPORTANT: Chronic Condition Detection Limitations\n    --------------------------------------------------\n    The chronic condition flags (has_diabetes, has_hypertension, has_heart_disease)\n    use simplified text matching on condition_description. This is NOT clinical-grade\n    detection and should be used for analytics/reporting only, not clinical decisions.\n\n    Detection patterns:\n    - Diabetes: description contains 'diabetes'\n    - Hypertension: description contains 'hypertension' or 'high blood pressure'\n    - Heart disease: description contains 'heart disease', 'cardiac', 'coronary',\n                     or 'atrial fibrillation'\n\n    For production clinical use, consider:\n    1. Using SNOMED codes instead of text matching\n    2. Implementing ICD-10 code mappings\n    3. Consulting clinical informaticists for proper condition groupings\n    4. Moving patterns to a seed file or reference table for maintainability\n#}\n\nwith patients as (\n    select\n        patient_id\n    from {{ ref('dim_patients') }}\n    where is_current = true\n),\n\nconditions as (\n    select\n        patient_id\n        , condition_start_date\n        , condition_end_date\n        , condition_code\n        , condition_description\n    from {{ ref('stg_synthea__conditions') }}\n),\n\ncondition_stats as (\n    select\n        patient_id\n        , count(*) as total_conditions\n        , sum(case when condition_end_date is null then 1 else 0 end) as active_conditions\n        , min(condition_start_date) as first_condition_date\n        , max(condition_start_date) as last_condition_date\n    from conditions\n    group by patient_id\n),\n\nchronic_flags as (\n    select\n        patient_id\n        , max(case\n            when lower(condition_description) like '%diabetes%' then 1\n            else 0\n        end) as has_diabetes\n        , max(case\n            when lower(condition_description) like '%hypertension%'\n                or lower(condition_description) like '%high blood pressure%' then 1\n            else 0\n        end) as has_hypertension\n        , max(case\n            when lower(condition_description) like '%heart disease%'\n                or lower(condition_description) like '%cardiac%'\n                or lower(condition_description) like '%coronary%'\n                or lower(condition_description) like '%atrial fibrillation%' then 1\n            else 0\n        end) as has_heart_disease\n    from conditions\n    group by patient_id\n),\n\nchronic_count as (\n    select\n        patient_id\n        , has_diabetes + has_hypertension + has_heart_disease as chronic_condition_count\n    from chronic_flags\n),\n\nfinal as (\n    select\n        p.patient_id\n        , coalesce(cs.total_conditions, 0) as total_conditions\n        , coalesce(cs.active_conditions, 0) as active_conditions\n        , cs.first_condition_date\n        , cs.last_condition_date\n        , coalesce(cast(cf.has_diabetes as boolean), false) as has_diabetes\n        , coalesce(cast(cf.has_hypertension as boolean), false) as has_hypertension\n        , coalesce(cast(cf.has_heart_disease as boolean), false) as has_heart_disease\n        , coalesce(cc.chronic_condition_count, 0) as chronic_condition_count\n    from patients p\n    left join condition_stats cs on p.patient_id = cs.patient_id\n    left join chronic_flags cf on p.patient_id = cf.patient_id\n    left join chronic_count cc on p.patient_id = cc.patient_id\n)\n\nselect * from final","tests":[],"is_recursive":false,"findings":[{"check":"join.left-null-propagation","tier":"high","instrument":"both","model_id":"model.healthcare_analytics.int_patients__with_conditions","construct":"left_join[final:condition_stats]","verdict":{"status":"uncovered"},"evidence":[{"label":"left join","value":"final — LEFT JOIN condition_stats ON patients.patient_id = condition_stats.patient_id"}],"recommendation":"Add a no-match given: one left-side row whose join key is absent from the right-side given rows, then extend `expect` with that row carrying NULL right-side columns (or the intended fallback). This finding's evidence carries a copy-pasteable given sketch.","pin_node":"final","sketches":["- input: ref('dim_patients')\n  rows:\n    - {patient_id: 404}   # 404 has no match below — the no-match path\n- input: ref('stg_synthea__conditions')\n  rows:\n    - {patient_id: 1}\n# expect: the no-match row with NULL stg_synthea__conditions columns (or the intended fallback)"]}]},{"name":"mart_date_state_grid","path":"models/marts/analytics/mart_date_state_grid.sql","description":"Dense month x state reporting scaffold.\nOne row per (calendar month x patient state) combination — the full\ncartesian product of dim_date months and the non-null states observed\nin patient staging. Left-join sparse activity facts against this grid\nso zero-activity cells render as explicit zeros.\nGrain: month_key x state\n\nUse cases:\n- Dense time-series dashboards (no missing month/state cells)\n- Zero-activity gap detection\n- cute-dbt cross-join CTE-edge demo (cute-dbt#64)\n","dag":{"nodes":[{"id":"months","role":"import"},{"id":"states","role":"import"},{"id":"grid","role":"transform"},{"id":"(final select)","label":"mart_date_state_grid.sql","role":"final"}],"edges":[{"from":"months","to":"grid","edge_type":"from"},{"from":"states","to":"grid","edge_type":"cross"},{"from":"grid","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from grid\n\n-- cute-dbt fixture: synthetic body mod","grid":"grid as (\n    select\n        cast(months.year_actual * 100 + months.month_actual as integer) as month_key\n        , months.year_actual\n        , months.month_actual\n        , months.month_name\n        , states.state\n    from months\n    cross join states\n)","months":"months as (\n    select distinct\n        year_actual\n        , month_actual\n        , month_name\n    from \"memory\".\"main_marts\".\"dim_date\"\n)","states":"states as (\n    select distinct state\n    from \"memory\".\"main_staging\".\"stg_synthea__patients\"\n    where state is not null\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        tags=['analytics', 'reporting']\n    )\n}}\n\n{#\n    Dense month x state reporting grid.\n\n    Cross joins every calendar month from dim_date with every non-null\n    patient state observed in staging. Left-join sparse activity facts\n    against this grid so zero-activity month/state cells render as\n    explicit zeros instead of silently disappearing from dashboards.\n\n    The explicit CROSS JOIN inside a CTE doubles as the cute-dbt\n    cross-join CTE-edge demo (cute-dbt#64).\n#}\n\nwith months as (\n    select distinct\n        year_actual\n        , month_actual\n        , month_name\n    from {{ ref('dim_date') }}\n),\n\nstates as (\n    select distinct state\n    from {{ ref('stg_synthea__patients') }}\n    where state is not null\n),\n\ngrid as (\n    select\n        cast(months.year_actual * 100 + months.month_actual as integer) as month_key\n        , months.year_actual\n        , months.month_actual\n        , months.month_name\n        , states.state\n    from months\n    cross join states\n)\n\nselect * from grid\n\n-- cute-dbt fixture: synthetic body mod","tests":[{"id":"unit_test.healthcare_analytics.mart_date_state_grid.test_mart_date_state_grid_cross_joins_months_and_states","name":"test_mart_date_state_grid_cross_joins_months_and_states","target_model":"mart_date_state_grid","changed":false,"description":"mart_date_state_grid CROSS JOINs the distinct calendar months from\ndim_date with the distinct non-null patient states from staging.\nThree daily dim_date rows collapse to two months; four patient\nrows collapse to two states (one NULL filtered out, one duplicate\ndeduplicated). The result is the full 2 x 2 cartesian product —\nfour grid rows. Mixes a dict given (dim_date) with a csv given\n(patients) in one test.\n","tags":[],"meta":{},"defined_in":"models/marts/analytics/_analytics__models.yml","given":[{"input":"ref('dim_date')","bound_to_node":"months","table":{"columns":["date_actual","month_actual","month_name","year_actual"],"rows":[{"cells":[{"display":"2024-01-15","key":{"t":"str","v":"2024-01-15"}},{"display":"1","key":{"t":"number","v":"1"}},{"display":"January","key":{"t":"str","v":"January"}},{"display":"2024","key":{"t":"number","v":"2024"}}]},{"cells":[{"display":"2024-01-16","key":{"t":"str","v":"2024-01-16"}},{"display":"1","key":{"t":"number","v":"1"}},{"display":"January","key":{"t":"str","v":"January"}},{"display":"2024","key":{"t":"number","v":"2024"}}]},{"cells":[{"display":"2024-02-01","key":{"t":"str","v":"2024-02-01"}},{"display":"2","key":{"t":"number","v":"2"}},{"display":"February","key":{"t":"str","v":"February"}},{"display":"2024","key":{"t":"number","v":"2024"}}]}]},"rows":[{"date_actual":"2024-01-15","month_actual":1,"month_name":"January","year_actual":2024},{"date_actual":"2024-01-16","month_actual":1,"month_name":"January","year_actual":2024},{"date_actual":"2024-02-01","month_actual":2,"month_name":"February","year_actual":2024}],"format":"dict","column_meta":{"date_actual":{"description":"The actual date value","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"},{"name":"unique"}]},"month_actual":{"description":"Month number (1-12)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},"month_name":{"description":"Full month name (e.g., January, February)","tests":[{"name":"not null"}]},"year_actual":{"description":"Year number","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]}}},{"input":"ref('stg_synthea__patients')","bound_to_node":"states","rows":null,"format":"csv","fixture":"tests/fixtures/mart_date_state_grid_patients.csv"}],"expected":{"table":{"columns":["month_actual","month_key","month_name","state","year_actual"],"rows":[{"cells":[{"display":"1","key":{"t":"number","v":"1"}},{"display":"202401","key":{"t":"number","v":"202401"}},{"display":"January","key":{"t":"str","v":"January"}},{"display":"Massachusetts","key":{"t":"str","v":"Massachusetts"}},{"display":"2024","key":{"t":"number","v":"2024"}}]},{"cells":[{"display":"1","key":{"t":"number","v":"1"}},{"display":"202401","key":{"t":"number","v":"202401"}},{"display":"January","key":{"t":"str","v":"January"}},{"display":"Connecticut","key":{"t":"str","v":"Connecticut"}},{"display":"2024","key":{"t":"number","v":"2024"}}]},{"cells":[{"display":"2","key":{"t":"number","v":"2"}},{"display":"202402","key":{"t":"number","v":"202402"}},{"display":"February","key":{"t":"str","v":"February"}},{"display":"Massachusetts","key":{"t":"str","v":"Massachusetts"}},{"display":"2024","key":{"t":"number","v":"2024"}}]},{"cells":[{"display":"2","key":{"t":"number","v":"2"}},{"display":"202402","key":{"t":"number","v":"202402"}},{"display":"February","key":{"t":"str","v":"February"}},{"display":"Connecticut","key":{"t":"str","v":"Connecticut"}},{"display":"2024","key":{"t":"number","v":"2024"}}]}]},"rows":[{"month_actual":"1","month_key":"202401","month_name":"January","state":"Massachusetts","year_actual":"2024"},{"month_actual":"1","month_key":"202401","month_name":"January","state":"Connecticut","year_actual":"2024"},{"month_actual":"2","month_key":"202402","month_name":"February","state":"Massachusetts","year_actual":"2024"},{"month_actual":"2","month_key":"202402","month_name":"February","state":"Connecticut","year_actual":"2024"}],"format":"csv","column_meta":{"month_actual":{"description":"Calendar month number (1-12) of the grid cell","tests":[{"name":"not null"}]},"month_key":{"description":"Month surrogate key in YYYYMM integer form (e.g., 202401)","tests":[{"name":"not null"}]},"month_name":{"description":"Full month name (e.g., January)"},"state":{"description":"Patient state, distinct and non-null from staging","tests":[{"name":"not null"}]},"year_actual":{"description":"Calendar year of the grid cell","tests":[{"name":"not null"}]}}}}],"is_recursive":false},{"name":"mart_dq_summary","path":"models/marts/analytics/mart_dq_summary.sql","description":"Data quality summary metrics for monitoring quarantine rates and validation failures.\nOne row per entity type (encounters, medications) with quarantine counts and failure breakdowns.\nGrain: entity_type\n\nUse cases:\n- Data quality monitoring dashboards\n- Quarantine rate trending\n- Validation failure root cause analysis\n- Data quality SLA tracking\n","dag":{"nodes":[{"id":"encounter_metrics","role":"import"},{"id":"medication_metrics","role":"import"},{"id":"combined_metrics","role":"transform"},{"id":"(final select)","label":"mart_dq_summary.sql","role":"final"}],"edges":[{"from":"encounter_metrics","to":"combined_metrics","edge_type":"union_all"},{"from":"medication_metrics","to":"combined_metrics","edge_type":"union_all"},{"from":"combined_metrics","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select\n    entity_type\n    , quarantined_count\n    , total_count\n    , quarantine_rate_pct\n    , failed_timestamp_validations\n    , failed_future_date_validations\n    , failed_historical_end_validations\n    , failed_historical_start_validations\n    , current_timestamp as _generated_at\nfrom combined_metrics\norder by entity_type\n\n-- cute-dbt fixture: synthetic body mod","combined_metrics":"combined_metrics as (\n    select\n        entity_type\n        , quarantined_count\n        , total_count\n        , quarantine_rate_pct\n        , failed_valid_encounter_timestamps as failed_timestamp_validations\n        , failed_no_future_encounter_dates as failed_future_date_validations\n        , failed_end_after_1900 as failed_historical_end_validations\n        , failed_start_after_1900 as failed_historical_start_validations\n    from encounter_metrics\n\n    union all\n\n    select\n        entity_type\n        , quarantined_count\n        , total_count\n        , quarantine_rate_pct\n        , failed_valid_medication_dates as failed_timestamp_validations\n        , failed_no_future_medication_dates as failed_future_date_validations\n        , failed_end_after_1900_if_present as failed_historical_end_validations\n        , failed_start_after_1900 as failed_historical_start_validations\n    from medication_metrics\n)","encounter_metrics":"encounter_metrics as (\n    select\n        'encounters' as entity_type\n        , count(*) filter (where is_dq_valid = false) as quarantined_count\n        , count(*) as total_count\n        , round(100.0 * count(*) filter (where is_dq_valid = false) / count(*), 2) as quarantine_rate_pct\n        , count(*) filter (where not valid_encounter_timestamps) as failed_valid_encounter_timestamps\n        , count(*) filter (where not no_future_encounter_dates) as failed_no_future_encounter_dates\n        , count(*) filter (where not end_after_1900) as failed_end_after_1900\n        , count(*) filter (where not start_after_1900) as failed_start_after_1900\n    from \"memory\".\"main_staging\".\"stg_synthea__encounters\"\n)","medication_metrics":"medication_metrics as (\n    select\n        'medications' as entity_type\n        , count(*) filter (where is_dq_valid = false) as quarantined_count\n        , count(*) as total_count\n        , round(100.0 * count(*) filter (where is_dq_valid = false) / count(*), 2) as quarantine_rate_pct\n        , count(*) filter (where not valid_medication_dates) as failed_valid_medication_dates\n        , count(*) filter (where not no_future_medication_dates) as failed_no_future_medication_dates\n        , count(*) filter (where not start_after_1900) as failed_start_after_1900\n        , count(*) filter (where not end_after_1900_if_present) as failed_end_after_1900_if_present\n    from \"memory\".\"main_staging\".\"stg_synthea__medications\"\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        tags=['analytics', 'data_quality']\n    )\n}}\n\nwith encounter_metrics as (\n    select\n        'encounters' as entity_type\n        , count(*) filter (where is_dq_valid = false) as quarantined_count\n        , count(*) as total_count\n        , round(100.0 * count(*) filter (where is_dq_valid = false) / count(*), 2) as quarantine_rate_pct\n        , count(*) filter (where not valid_encounter_timestamps) as failed_valid_encounter_timestamps\n        , count(*) filter (where not no_future_encounter_dates) as failed_no_future_encounter_dates\n        , count(*) filter (where not end_after_1900) as failed_end_after_1900\n        , count(*) filter (where not start_after_1900) as failed_start_after_1900\n    from {{ ref('stg_synthea__encounters') }}\n),\n\nmedication_metrics as (\n    select\n        'medications' as entity_type\n        , count(*) filter (where is_dq_valid = false) as quarantined_count\n        , count(*) as total_count\n        , round(100.0 * count(*) filter (where is_dq_valid = false) / count(*), 2) as quarantine_rate_pct\n        , count(*) filter (where not valid_medication_dates) as failed_valid_medication_dates\n        , count(*) filter (where not no_future_medication_dates) as failed_no_future_medication_dates\n        , count(*) filter (where not start_after_1900) as failed_start_after_1900\n        , count(*) filter (where not end_after_1900_if_present) as failed_end_after_1900_if_present\n    from {{ ref('stg_synthea__medications') }}\n),\n\ncombined_metrics as (\n    select\n        entity_type\n        , quarantined_count\n        , total_count\n        , quarantine_rate_pct\n        , failed_valid_encounter_timestamps as failed_timestamp_validations\n        , failed_no_future_encounter_dates as failed_future_date_validations\n        , failed_end_after_1900 as failed_historical_end_validations\n        , failed_start_after_1900 as failed_historical_start_validations\n    from encounter_metrics\n\n    union all\n\n    select\n        entity_type\n        , quarantined_count\n        , total_count\n        , quarantine_rate_pct\n        , failed_valid_medication_dates as failed_timestamp_validations\n        , failed_no_future_medication_dates as failed_future_date_validations\n        , failed_end_after_1900_if_present as failed_historical_end_validations\n        , failed_start_after_1900 as failed_historical_start_validations\n    from medication_metrics\n)\n\nselect\n    entity_type\n    , quarantined_count\n    , total_count\n    , quarantine_rate_pct\n    , failed_timestamp_validations\n    , failed_future_date_validations\n    , failed_historical_end_validations\n    , failed_historical_start_validations\n    , current_timestamp as _generated_at\nfrom combined_metrics\norder by entity_type\n\n-- cute-dbt fixture: synthetic body mod","tests":[{"id":"unit_test.healthcare_analytics.mart_dq_summary.test_mart_dq_summary_combines_encounter_and_medication_metrics","name":"test_mart_dq_summary_combines_encounter_and_medication_metrics","target_model":"mart_dq_summary","changed":false,"description":"mart_dq_summary UNION-ALLs metrics from stg_synthea__encounters\nand stg_synthea__medications. This test mocks two encounter rows\n(one invalid) and two medication rows (both invalid), then asserts\nthe per-entity counts + quarantine rate. Uses csv format for both\nGIVEN and EXPECT — compact tabular form across many boolean\ndq-flag columns.\n","tags":[],"meta":{},"defined_in":"models/marts/analytics/_analytics__models.yml","given":[{"input":"ref('stg_synthea__encounters')","bound_to_node":"encounter_metrics","table":{"columns":["end_after_1900","is_dq_valid","no_future_encounter_dates","start_after_1900","valid_encounter_timestamps"],"rows":[{"cells":[{"display":"true","key":{"t":"bool","v":true}},{"display":"false","key":{"t":"bool","v":false}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"false","key":{"t":"bool","v":false}}]},{"cells":[{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}}]}]},"rows":[{"end_after_1900":"true","is_dq_valid":"false","no_future_encounter_dates":"true","start_after_1900":"true","valid_encounter_timestamps":"false"},{"end_after_1900":"true","is_dq_valid":"true","no_future_encounter_dates":"true","start_after_1900":"true","valid_encounter_timestamps":"true"}],"format":"csv"},{"input":"ref('stg_synthea__medications')","bound_to_node":"medication_metrics","table":{"columns":["end_after_1900_if_present","is_dq_valid","no_future_medication_dates","start_after_1900","valid_medication_dates"],"rows":[{"cells":[{"display":"true","key":{"t":"bool","v":true}},{"display":"false","key":{"t":"bool","v":false}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"false","key":{"t":"bool","v":false}}]},{"cells":[{"display":"true","key":{"t":"bool","v":true}},{"display":"false","key":{"t":"bool","v":false}},{"display":"false","key":{"t":"bool","v":false}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}}]}]},"rows":[{"end_after_1900_if_present":"true","is_dq_valid":"false","no_future_medication_dates":"true","start_after_1900":"true","valid_medication_dates":"false"},{"end_after_1900_if_present":"true","is_dq_valid":"false","no_future_medication_dates":"false","start_after_1900":"true","valid_medication_dates":"true"}],"format":"csv"}],"expected":{"table":{"columns":["entity_type","failed_timestamp_validations","quarantine_rate_pct","quarantined_count","total_count"],"rows":[{"cells":[{"display":"encounters","key":{"t":"str","v":"encounters"}},{"display":"1","key":{"t":"number","v":"1"}},{"display":"50.00","key":{"t":"number","v":"50"}},{"display":"1","key":{"t":"number","v":"1"}},{"display":"2","key":{"t":"number","v":"2"}}]},{"cells":[{"display":"medications","key":{"t":"str","v":"medications"}},{"display":"1","key":{"t":"number","v":"1"}},{"display":"100.00","key":{"t":"number","v":"100"}},{"display":"2","key":{"t":"number","v":"2"}},{"display":"2","key":{"t":"number","v":"2"}}]}]},"rows":[{"entity_type":"encounters","failed_timestamp_validations":"1","quarantine_rate_pct":"50.00","quarantined_count":"1","total_count":"2"},{"entity_type":"medications","failed_timestamp_validations":"1","quarantine_rate_pct":"100.00","quarantined_count":"2","total_count":"2"}],"format":"csv","column_meta":{"entity_type":{"description":"Type of entity being measured (encounters, medications)","tests":[{"name":"accepted values","values":["encounters","medications"]},{"name":"not null"}]},"failed_timestamp_validations":{"description":"Count of records failing timestamp/date sequence validations"},"quarantine_rate_pct":{"description":"Percentage of records quarantined (quarantined_count / total_count * 100)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},"quarantined_count":{"description":"Number of records failing data quality validations","tests":[{"name":"not null"}]},"total_count":{"description":"Total number of records (valid + quarantined)","tests":[{"name":"not null"}]}}}},{"id":"unit_test.healthcare_analytics.mart_dq_summary.test_mart_dq_summary_zero_quarantined_when_all_valid","name":"test_mart_dq_summary_zero_quarantined_when_all_valid","target_model":"mart_dq_summary","changed":false,"description":"mart_dq_summary should report zero quarantined_count and 0.00\nquarantine_rate_pct when every upstream row passes data-quality\nvalidations. Uses sql format for the GIVEN mocks and dict format\nfor the EXPECT — dict expects only compare listed columns, so\nnon-deterministic outputs (`_generated_at` from\n`current_timestamp`) are excluded from comparison.\n","tags":[],"meta":{},"defined_in":"models/marts/analytics/_analytics__models.yml","given":[{"input":"ref('stg_synthea__encounters')","bound_to_node":"encounter_metrics","table":{"columns":["is_dq_valid","valid_encounter_timestamps","no_future_encounter_dates","end_after_1900","start_after_1900"],"rows":[{"cells":[{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}}]}]},"rows":"select\n  true as is_dq_valid\n  , true as valid_encounter_timestamps\n  , true as no_future_encounter_dates\n  , true as end_after_1900\n  , true as start_after_1900","format":"sql"},{"input":"ref('stg_synthea__medications')","bound_to_node":"medication_metrics","table":{"columns":["is_dq_valid","valid_medication_dates","no_future_medication_dates","start_after_1900","end_after_1900_if_present"],"rows":[{"cells":[{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}},{"display":"true","key":{"t":"bool","v":true}}]}]},"rows":"select\n  true as is_dq_valid\n  , true as valid_medication_dates\n  , true as no_future_medication_dates\n  , true as start_after_1900\n  , true as end_after_1900_if_present","format":"sql"}],"expected":{"table":{"columns":["entity_type","quarantine_rate_pct","quarantined_count","total_count"],"rows":[{"cells":[{"display":"encounters","key":{"t":"str","v":"encounters"}},{"display":"0.0","key":{"t":"number","v":"0"}},{"display":"0","key":{"t":"number","v":"0"}},{"display":"1","key":{"t":"number","v":"1"}}]},{"cells":[{"display":"medications","key":{"t":"str","v":"medications"}},{"display":"0.0","key":{"t":"number","v":"0"}},{"display":"0","key":{"t":"number","v":"0"}},{"display":"1","key":{"t":"number","v":"1"}}]}]},"rows":[{"entity_type":"encounters","quarantine_rate_pct":0.0,"quarantined_count":0,"total_count":1},{"entity_type":"medications","quarantine_rate_pct":0.0,"quarantined_count":0,"total_count":1}],"format":"dict","column_meta":{"entity_type":{"description":"Type of entity being measured (encounters, medications)","tests":[{"name":"accepted values","values":["encounters","medications"]},{"name":"not null"}]},"quarantine_rate_pct":{"description":"Percentage of records quarantined (quarantined_count / total_count * 100)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},"quarantined_count":{"description":"Number of records failing data quality validations","tests":[{"name":"not null"}]},"total_count":{"description":"Total number of records (valid + quarantined)","tests":[{"name":"not null"}]}}}}],"is_recursive":false,"findings":[{"check":"grain.unique-key-unbacked","tier":"total","instrument":"data-test","model_id":"model.healthcare_analytics.mart_dq_summary","construct":"config.unique_key","verdict":{"status":"uncovered"},"evidence":[{"label":"unique_key","value":"entity_type"}],"recommendation":"Add a uniqueness data test at the declared grain: `unique` on a single-column key, or `dbt_utils.unique_combination_of_columns` over the composite key columns.","pin_node":"(final select)"},{"check":"union.arm-coverage","tier":"high","instrument":"unit-test","model_id":"model.healthcare_analytics.mart_dq_summary","construct":"union[combined_metrics]","verdict":{"status":"covered","by":["unit_test.healthcare_analytics.mart_dq_summary.test_mart_dq_summary_combines_encounter_and_medication_metrics","unit_test.healthcare_analytics.mart_dq_summary.test_mart_dq_summary_zero_quarantined_when_all_valid"]},"evidence":[{"label":"union","value":"combined_metrics (2 arms: encounter_metrics, medication_metrics)"}],"pin_node":"combined_metrics"}]},{"name":"stg_synthea__conditions","path":"models/staging/synthea/stg_synthea__conditions.sql","description":"Staging model for patient conditions/diagnoses. One row per condition instance with surrogate key.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_surrogate_key","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__conditions.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_surrogate_key","edge_type":"from"},{"from":"with_surrogate_key","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_surrogate_key\n)","renamed":"renamed as (\n    select\n        -- foreign keys\n        PATIENT as patient_id\n        , ENCOUNTER as encounter_id\n\n        -- dates\n        , START as condition_start_date\n        , STOP as condition_end_date\n\n        -- condition details\n        , CODE as condition_code\n        , DESCRIPTION as condition_description\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"conditions\"\n)","with_surrogate_key":"with_surrogate_key as (\n    select\n        -- surrogate primary key (no natural key exists)\n        md5(cast(coalesce(cast(patient_id as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(encounter_id as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(condition_code as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(condition_start_date as TEXT), '_dbt_utils_surrogate_key_null_') as TEXT)) as condition_id\n        , *\n    from renamed\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'conditions') }}\n),\n\nrenamed as (\n    select\n        -- foreign keys\n        PATIENT as patient_id\n        , ENCOUNTER as encounter_id\n\n        -- dates\n        , START as condition_start_date\n        , STOP as condition_end_date\n\n        -- condition details\n        , CODE as condition_code\n        , DESCRIPTION as condition_description\n    from source\n),\n\nwith_surrogate_key as (\n    select\n        -- surrogate primary key (no natural key exists)\n        {{ dbt_utils.generate_surrogate_key(['patient_id', 'encounter_id', 'condition_code', 'condition_start_date']) }} as condition_id\n        , *\n    from renamed\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_surrogate_key\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"stg_synthea__encounters","path":"models/staging/synthea/stg_synthea__encounters.sql","description":"Staging model for healthcare encounters/visits. One row per encounter with patient, provider, organization, and payer relationships.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_dq_flags","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__encounters.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_dq_flags","edge_type":"from"},{"from":"with_dq_flags","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_dq_flags\n)","renamed":"renamed as (\n    select\n        -- primary key\n        Id as encounter_id\n\n        -- foreign keys\n        , PATIENT as patient_id\n        , ORGANIZATION as organization_id\n        , PROVIDER as provider_id\n        , PAYER as payer_id\n\n        -- timestamps\n        , cast(START as timestamp) as encounter_start_at\n        , cast(STOP as timestamp) as encounter_end_at\n\n        -- attributes\n        , ENCOUNTERCLASS as encounter_class\n        , CODE as encounter_code\n        , DESCRIPTION as encounter_description\n\n        -- costs\n        , BASE_ENCOUNTER_COST as base_encounter_cost\n        , TOTAL_CLAIM_COST as total_claim_cost\n        , PAYER_COVERAGE as payer_coverage\n\n        -- reason for visit\n        , REASONCODE as reason_code\n        , REASONDESCRIPTION as reason_description\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"encounters\"\n)","with_dq_flags":"with_dq_flags as (\n    \n    select\n        *\n\n        -- individual validation flags\n        \n        , (encounter_end_at >= encounter_start_at) as valid_encounter_timestamps\n        \n        , (encounter_start_at <= current_timestamp) as no_future_encounter_dates\n        \n        , (encounter_end_at >= timestamp '1900-01-01') as end_after_1900\n        \n        , (encounter_start_at >= timestamp '1900-01-01') as start_after_1900\n        \n\n        -- overall validity flag\n        , \n    (\n        \n        (encounter_end_at >= encounter_start_at)\n         and \n        \n        (encounter_start_at <= current_timestamp)\n         and \n        \n        (encounter_end_at >= timestamp '1900-01-01')\n         and \n        \n        (encounter_start_at >= timestamp '1900-01-01')\n        \n        \n    )\n as is_dq_valid\n\n        -- array of failed test names\n        , \n    list_value(\n        \n        case when not (encounter_end_at >= encounter_start_at) then 'valid_encounter_timestamps' else null end\n        , \n        \n        case when not (encounter_start_at <= current_timestamp) then 'no_future_encounter_dates' else null end\n        , \n        \n        case when not (encounter_end_at >= timestamp '1900-01-01') then 'end_after_1900' else null end\n        , \n        \n        case when not (encounter_start_at >= timestamp '1900-01-01') then 'start_after_1900' else null end\n        \n        \n    )\n as failed_dq_tests\n\n    from renamed\n\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'encounters') }}\n),\n\nrenamed as (\n    select\n        -- primary key\n        Id as encounter_id\n\n        -- foreign keys\n        , PATIENT as patient_id\n        , ORGANIZATION as organization_id\n        , PROVIDER as provider_id\n        , PAYER as payer_id\n\n        -- timestamps\n        , cast(START as timestamp) as encounter_start_at\n        , cast(STOP as timestamp) as encounter_end_at\n\n        -- attributes\n        , ENCOUNTERCLASS as encounter_class\n        , CODE as encounter_code\n        , DESCRIPTION as encounter_description\n\n        -- costs\n        , BASE_ENCOUNTER_COST as base_encounter_cost\n        , TOTAL_CLAIM_COST as total_claim_cost\n        , PAYER_COVERAGE as payer_coverage\n\n        -- reason for visit\n        , REASONCODE as reason_code\n        , REASONDESCRIPTION as reason_description\n    from source\n),\n\nwith_dq_flags as (\n    {{ add_dq_flags(\n        source_cte='renamed',\n        validations={\n            'valid_encounter_timestamps': 'encounter_end_at >= encounter_start_at',\n            'no_future_encounter_dates': 'encounter_start_at <= current_timestamp',\n            'end_after_1900': 'encounter_end_at >= timestamp \\'1900-01-01\\'',\n            'start_after_1900': 'encounter_start_at >= timestamp \\'1900-01-01\\''\n        }\n    ) }}\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_dq_flags\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"stg_synthea__medications","path":"models/staging/synthea/stg_synthea__medications.sql","description":"Staging model for prescribed medications. One row per medication prescription with surrogate key.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_row_number","role":"transform"},{"id":"with_surrogate_key","role":"transform"},{"id":"with_dq_flags","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__medications.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_row_number","edge_type":"from"},{"from":"with_row_number","to":"with_surrogate_key","edge_type":"from"},{"from":"with_surrogate_key","to":"with_dq_flags","edge_type":"from"},{"from":"with_dq_flags","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_dq_flags\n)","renamed":"renamed as (\n    select\n        -- foreign keys\n        PATIENT as patient_id\n        , PAYER as payer_id\n        , ENCOUNTER as encounter_id\n\n        -- timestamps\n        , cast(START as timestamp) as medication_start_at\n        , cast(STOP as timestamp) as medication_end_at\n\n        -- medication details\n        , CODE as medication_code\n        , DESCRIPTION as medication_description\n\n        -- costs\n        , BASE_COST as base_cost\n        , PAYER_COVERAGE as payer_coverage\n        , DISPENSES as dispenses\n        , TOTALCOST as total_cost\n\n        -- reason for medication\n        , REASONCODE as reason_code\n        , REASONDESCRIPTION as reason_description\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"medications\"\n)","with_dq_flags":"with_dq_flags as (\n    \n    select\n        *\n\n        -- individual validation flags\n        \n        , (medication_end_at is null or medication_end_at >= medication_start_at) as valid_medication_dates\n        \n        , (cast(medication_start_at as date) <= current_date) as no_future_medication_dates\n        \n        , (medication_start_at >= timestamp '1900-01-01') as start_after_1900\n        \n        , (medication_end_at is null or medication_end_at >= timestamp '1900-01-01') as end_after_1900_if_present\n        \n\n        -- overall validity flag\n        , \n    (\n        \n        (medication_end_at is null or medication_end_at >= medication_start_at)\n         and \n        \n        (cast(medication_start_at as date) <= current_date)\n         and \n        \n        (medication_start_at >= timestamp '1900-01-01')\n         and \n        \n        (medication_end_at is null or medication_end_at >= timestamp '1900-01-01')\n        \n        \n    )\n as is_dq_valid\n\n        -- array of failed test names\n        , \n    list_value(\n        \n        case when not (medication_end_at is null or medication_end_at >= medication_start_at) then 'valid_medication_dates' else null end\n        , \n        \n        case when not (cast(medication_start_at as date) <= current_date) then 'no_future_medication_dates' else null end\n        , \n        \n        case when not (medication_start_at >= timestamp '1900-01-01') then 'start_after_1900' else null end\n        , \n        \n        case when not (medication_end_at is null or medication_end_at >= timestamp '1900-01-01') then 'end_after_1900_if_present' else null end\n        \n        \n    )\n as failed_dq_tests\n\n    from with_surrogate_key\n\n)","with_row_number":"with_row_number as (\n    select\n        *\n        , row_number() over (\n            partition by patient_id, encounter_id, medication_code, medication_start_at\n            order by medication_end_at asc nulls last, total_cost desc\n        ) as _row_num\n    from renamed\n)","with_surrogate_key":"with_surrogate_key as (\n    select\n        -- surrogate primary key (includes row_num for true duplicates)\n        md5(cast(coalesce(cast(patient_id as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(encounter_id as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(medication_code as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(medication_start_at as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(_row_num as TEXT), '_dbt_utils_surrogate_key_null_') as TEXT)) as medication_id\n        , patient_id\n        , payer_id\n        , encounter_id\n        , medication_start_at\n        , medication_end_at\n        , medication_code\n        , medication_description\n        , base_cost\n        , payer_coverage\n        , dispenses\n        , total_cost\n        , reason_code\n        , reason_description\n    from with_row_number\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'medications') }}\n),\n\nrenamed as (\n    select\n        -- foreign keys\n        PATIENT as patient_id\n        , PAYER as payer_id\n        , ENCOUNTER as encounter_id\n\n        -- timestamps\n        , cast(START as timestamp) as medication_start_at\n        , cast(STOP as timestamp) as medication_end_at\n\n        -- medication details\n        , CODE as medication_code\n        , DESCRIPTION as medication_description\n\n        -- costs\n        , BASE_COST as base_cost\n        , PAYER_COVERAGE as payer_coverage\n        , DISPENSES as dispenses\n        , TOTALCOST as total_cost\n\n        -- reason for medication\n        , REASONCODE as reason_code\n        , REASONDESCRIPTION as reason_description\n    from source\n),\n\nwith_row_number as (\n    select\n        *\n        , row_number() over (\n            partition by patient_id, encounter_id, medication_code, medication_start_at\n            order by medication_end_at asc nulls last, total_cost desc\n        ) as _row_num\n    from renamed\n),\n\nwith_surrogate_key as (\n    select\n        -- surrogate primary key (includes row_num for true duplicates)\n        {{ dbt_utils.generate_surrogate_key(['patient_id', 'encounter_id', 'medication_code', 'medication_start_at', '_row_num']) }} as medication_id\n        , patient_id\n        , payer_id\n        , encounter_id\n        , medication_start_at\n        , medication_end_at\n        , medication_code\n        , medication_description\n        , base_cost\n        , payer_coverage\n        , dispenses\n        , total_cost\n        , reason_code\n        , reason_description\n    from with_row_number\n),\n\nwith_dq_flags as (\n    {{ add_dq_flags(\n        source_cte='with_surrogate_key',\n        validations={\n            'valid_medication_dates': 'medication_end_at is null or medication_end_at >= medication_start_at',\n            'no_future_medication_dates': 'cast(medication_start_at as date) <= current_date',\n            'start_after_1900': 'medication_start_at >= timestamp \\'1900-01-01\\'',\n            'end_after_1900_if_present': 'medication_end_at is null or medication_end_at >= timestamp \\'1900-01-01\\''\n        }\n    ) }}\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_dq_flags\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"stg_synthea__observations","path":"models/staging/synthea/stg_synthea__observations.sql","description":"Staging model for clinical observations (vital signs, lab results). One row per observation with surrogate key.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_row_number","role":"transform"},{"id":"with_surrogate_key","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__observations.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_row_number","edge_type":"from"},{"from":"with_row_number","to":"with_surrogate_key","edge_type":"from"},{"from":"with_surrogate_key","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_surrogate_key\n)","renamed":"renamed as (\n    select\n        -- foreign keys\n        PATIENT as patient_id\n        , ENCOUNTER as encounter_id\n\n        -- timestamp\n        , cast(DATE as timestamp) as observation_at\n\n        -- observation details\n        , CODE as observation_code\n        , DESCRIPTION as observation_description\n        , VALUE as observation_value\n        , UNITS as units\n        , TYPE as observation_type\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"observations\"\n)","with_row_number":"with_row_number as (\n    select\n        *\n        , row_number() over (\n            partition by patient_id, encounter_id, observation_code, observation_at\n            order by observation_value, observation_description\n        ) as _row_num\n    from renamed\n)","with_surrogate_key":"with_surrogate_key as (\n    select\n        -- surrogate primary key (includes row_num for true duplicates)\n        md5(cast(coalesce(cast(patient_id as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(encounter_id as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(observation_code as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(observation_at as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(_row_num as TEXT), '_dbt_utils_surrogate_key_null_') as TEXT)) as observation_id\n        , patient_id\n        , encounter_id\n        , observation_at\n        , observation_code\n        , observation_description\n        , observation_value\n        , units\n        , observation_type\n    from with_row_number\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'observations') }}\n),\n\nrenamed as (\n    select\n        -- foreign keys\n        PATIENT as patient_id\n        , ENCOUNTER as encounter_id\n\n        -- timestamp\n        , cast(DATE as timestamp) as observation_at\n\n        -- observation details\n        , CODE as observation_code\n        , DESCRIPTION as observation_description\n        , VALUE as observation_value\n        , UNITS as units\n        , TYPE as observation_type\n    from source\n),\n\nwith_row_number as (\n    select\n        *\n        , row_number() over (\n            partition by patient_id, encounter_id, observation_code, observation_at\n            order by observation_value, observation_description\n        ) as _row_num\n    from renamed\n),\n\nwith_surrogate_key as (\n    select\n        -- surrogate primary key (includes row_num for true duplicates)\n        {{ dbt_utils.generate_surrogate_key(['patient_id', 'encounter_id', 'observation_code', 'observation_at', '_row_num']) }} as observation_id\n        , patient_id\n        , encounter_id\n        , observation_at\n        , observation_code\n        , observation_description\n        , observation_value\n        , units\n        , observation_type\n    from with_row_number\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_surrogate_key\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"stg_synthea__organizations","path":"models/staging/synthea/stg_synthea__organizations.sql","description":"Staging model for healthcare organizations/facilities. One row per organization with location and performance metrics.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__organizations.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from renamed\n)","renamed":"renamed as (\n    select\n        -- primary key\n        Id as organization_id\n\n        -- attributes\n        , NAME as organization_name\n        , ADDRESS as address\n        , CITY as city\n        , STATE as state\n        , ZIP as zip_code\n        , PHONE as phone\n\n        -- location\n        , LAT as latitude\n        , LON as longitude\n\n        -- metrics\n        , REVENUE as revenue\n        , UTILIZATION as utilization\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"organizations\"\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'organizations') }}\n),\n\nrenamed as (\n    select\n        -- primary key\n        Id as organization_id\n\n        -- attributes\n        , NAME as organization_name\n        , ADDRESS as address\n        , CITY as city\n        , STATE as state\n        , ZIP as zip_code\n        , PHONE as phone\n\n        -- location\n        , LAT as latitude\n        , LON as longitude\n\n        -- metrics\n        , REVENUE as revenue\n        , UTILIZATION as utilization\n    from source\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from renamed\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"stg_synthea__patients","path":"models/staging/synthea/stg_synthea__patients.sql","description":"Staging model for patient demographics and identifiers. One row per patient with personal information, location, and financial data.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__patients.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final\n\n-- cute-dbt fixture: synthetic body mod","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from renamed\n)","renamed":"renamed as (\n    select\n        -- primary key\n        Id as patient_id\n\n        -- demographics\n        , FIRST as first_name\n        , LAST as last_name\n        , PREFIX as name_prefix\n        , SUFFIX as name_suffix\n        , MAIDEN as maiden_name\n        , GENDER as gender\n        , RACE as race\n        , ETHNICITY as ethnicity\n        , MARITAL as marital_status\n\n        -- dates\n        , BIRTHDATE as birth_date\n        , DEATHDATE as death_date\n\n        -- identifiers (hashed for privacy)\n        , md5(SSN) as ssn_hash\n        , DRIVERS as drivers_license\n        , PASSPORT as passport_number\n\n        -- location\n        , BIRTHPLACE as birth_place\n        , ADDRESS as address\n        , CITY as city\n        , STATE as state\n        , COUNTY as county\n        , ZIP as zip_code\n        , LAT as latitude\n        , LON as longitude\n\n        -- financial\n        , HEALTHCARE_EXPENSES as healthcare_expenses\n        , HEALTHCARE_COVERAGE as healthcare_coverage\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"patients\"\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'patients') }}\n),\n\nrenamed as (\n    select\n        -- primary key\n        Id as patient_id\n\n        -- demographics\n        , FIRST as first_name\n        , LAST as last_name\n        , PREFIX as name_prefix\n        , SUFFIX as name_suffix\n        , MAIDEN as maiden_name\n        , GENDER as gender\n        , RACE as race\n        , ETHNICITY as ethnicity\n        , MARITAL as marital_status\n\n        -- dates\n        , BIRTHDATE as birth_date\n        , DEATHDATE as death_date\n\n        -- identifiers (hashed for privacy)\n        , md5(SSN) as ssn_hash\n        , DRIVERS as drivers_license\n        , PASSPORT as passport_number\n\n        -- location\n        , BIRTHPLACE as birth_place\n        , ADDRESS as address\n        , CITY as city\n        , STATE as state\n        , COUNTY as county\n        , ZIP as zip_code\n        , LAT as latitude\n        , LON as longitude\n\n        -- financial\n        , HEALTHCARE_EXPENSES as healthcare_expenses\n        , HEALTHCARE_COVERAGE as healthcare_coverage\n    from source\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from renamed\n)\n\nselect * from final\n\n-- cute-dbt fixture: synthetic body mod","tests":[{"id":"unit_test.healthcare_analytics.stg_synthea__patients.test_stg_synthea__patients_renames_and_hashes_source_columns","name":"test_stg_synthea__patients_renames_and_hashes_source_columns","target_model":"stg_synthea__patients","changed":false,"description":"stg_synthea__patients renames the raw Synthea UPPERCASE columns to\nsnake_case and hashes the SSN with md5. The given mocks the\nsynthea_raw.patients SOURCE directly (inline dict rows) — the only\nunit test in this project whose input is a source() rather than a\nref() (cute-dbt#57). Dict expect compares listed columns only, so\nthe non-deterministic _loaded_at (current_timestamp) is excluded\nfrom assertion automatically.\n","tags":[],"meta":{},"defined_in":"models/staging/synthea/_synthea__models.yml","given":[{"input":"source('synthea_raw', 'patients')","bound_to_node":"source","table":{"columns":["CITY","FIRST","GENDER","Id","LAST","SSN","STATE"],"rows":[{"cells":[{"display":"Boston","key":{"t":"str","v":"Boston"}},{"display":"Ada","key":{"t":"str","v":"Ada"}},{"display":"F","key":{"t":"str","v":"F"}},{"display":"c0000000-0000-0000-0000-000000000001","key":{"t":"str","v":"c0000000-0000-0000-0000-000000000001"}},{"display":"Lovelace","key":{"t":"str","v":"Lovelace"}},{"display":"999-99-9999","key":{"t":"str","v":"999-99-9999"}},{"display":"Massachusetts","key":{"t":"str","v":"Massachusetts"}}]}]},"rows":[{"CITY":"Boston","FIRST":"Ada","GENDER":"F","Id":"c0000000-0000-0000-0000-000000000001","LAST":"Lovelace","SSN":"999-99-9999","STATE":"Massachusetts"}],"format":"dict"}],"expected":{"table":{"columns":["city","first_name","gender","last_name","patient_id","ssn_hash","state"],"rows":[{"cells":[{"display":"Boston","key":{"t":"str","v":"Boston"}},{"display":"Ada","key":{"t":"str","v":"Ada"}},{"display":"F","key":{"t":"str","v":"F"}},{"display":"Lovelace","key":{"t":"str","v":"Lovelace"}},{"display":"c0000000-0000-0000-0000-000000000001","key":{"t":"str","v":"c0000000-0000-0000-0000-000000000001"}},{"display":"257cf696294931925796925d89aa0afb","key":{"t":"str","v":"257cf696294931925796925d89aa0afb"}},{"display":"Massachusetts","key":{"t":"str","v":"Massachusetts"}}]}]},"rows":[{"city":"Boston","first_name":"Ada","gender":"F","last_name":"Lovelace","patient_id":"c0000000-0000-0000-0000-000000000001","ssn_hash":"257cf696294931925796925d89aa0afb","state":"Massachusetts"}],"format":"dict","column_meta":{"city":{"description":"City of residence"},"first_name":{"description":"Patient's first name","tests":[{"name":"not null"}]},"gender":{"description":"Patient gender (M or F)","tests":[{"name":"accepted values","values":["M","F"]},{"name":"dbt_expectations.expect_column_values_to_match_regex"},{"name":"not null"}]},"last_name":{"description":"Patient's last name","tests":[{"name":"not null"}]},"patient_id":{"description":"Unique patient identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},"ssn_hash":{"description":"MD5 hash of Social Security Number (masked for privacy)"},"state":{"description":"State of residence (full state name, e.g., Massachusetts)"}}}}],"is_recursive":false},{"name":"stg_synthea__payers","path":"models/staging/synthea/stg_synthea__payers.sql","description":"Staging model for insurance payers. One row per payer with contact information and aggregate metrics.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__payers.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from renamed\n)","renamed":"renamed as (\n    select\n        -- primary key\n        Id as payer_id\n\n        -- attributes\n        , NAME as payer_name\n        , ADDRESS as address\n        , CITY as city\n        , STATE_HEADQUARTERED as state\n        , ZIP as zip_code\n        , PHONE as phone\n\n        -- financial metrics\n        , AMOUNT_COVERED as amount_covered\n        , AMOUNT_UNCOVERED as amount_uncovered\n        , REVENUE as revenue\n\n        -- utilization metrics\n        , COVERED_ENCOUNTERS as covered_encounters\n        , UNCOVERED_ENCOUNTERS as uncovered_encounters\n        , COVERED_MEDICATIONS as covered_medications\n        , UNCOVERED_MEDICATIONS as uncovered_medications\n        , COVERED_PROCEDURES as covered_procedures\n        , UNCOVERED_PROCEDURES as uncovered_procedures\n        , COVERED_IMMUNIZATIONS as covered_immunizations\n        , UNCOVERED_IMMUNIZATIONS as uncovered_immunizations\n\n        -- member metrics\n        , UNIQUE_CUSTOMERS as unique_customers\n        , QOLS_AVG as average_quality_of_life_score\n        , MEMBER_MONTHS as member_months\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"payers\"\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'payers') }}\n),\n\nrenamed as (\n    select\n        -- primary key\n        Id as payer_id\n\n        -- attributes\n        , NAME as payer_name\n        , ADDRESS as address\n        , CITY as city\n        , STATE_HEADQUARTERED as state\n        , ZIP as zip_code\n        , PHONE as phone\n\n        -- financial metrics\n        , AMOUNT_COVERED as amount_covered\n        , AMOUNT_UNCOVERED as amount_uncovered\n        , REVENUE as revenue\n\n        -- utilization metrics\n        , COVERED_ENCOUNTERS as covered_encounters\n        , UNCOVERED_ENCOUNTERS as uncovered_encounters\n        , COVERED_MEDICATIONS as covered_medications\n        , UNCOVERED_MEDICATIONS as uncovered_medications\n        , COVERED_PROCEDURES as covered_procedures\n        , UNCOVERED_PROCEDURES as uncovered_procedures\n        , COVERED_IMMUNIZATIONS as covered_immunizations\n        , UNCOVERED_IMMUNIZATIONS as uncovered_immunizations\n\n        -- member metrics\n        , UNIQUE_CUSTOMERS as unique_customers\n        , QOLS_AVG as average_quality_of_life_score\n        , MEMBER_MONTHS as member_months\n    from source\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from renamed\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"stg_synthea__procedures","path":"models/staging/synthea/stg_synthea__procedures.sql","description":"Staging model for medical procedures performed. One row per procedure instance with surrogate key.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"with_surrogate_key","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__procedures.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"with_surrogate_key","edge_type":"from"},{"from":"with_surrogate_key","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_surrogate_key\n)","renamed":"renamed as (\n    select\n        -- foreign keys\n        PATIENT as patient_id\n        , ENCOUNTER as encounter_id\n\n        -- timestamp\n        , cast(DATE as timestamp) as procedure_at\n\n        -- procedure details\n        , CODE as procedure_code\n        , DESCRIPTION as procedure_description\n        , BASE_COST as base_cost\n\n        -- reason for procedure\n        , REASONCODE as reason_code\n        , REASONDESCRIPTION as reason_description\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"procedures\"\n)","with_surrogate_key":"with_surrogate_key as (\n    select\n        -- surrogate primary key (no natural key exists)\n        md5(cast(coalesce(cast(patient_id as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(encounter_id as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(procedure_code as TEXT), '_dbt_utils_surrogate_key_null_') || '-' || coalesce(cast(procedure_at as TEXT), '_dbt_utils_surrogate_key_null_') as TEXT)) as procedure_id\n        , *\n    from renamed\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'procedures') }}\n),\n\nrenamed as (\n    select\n        -- foreign keys\n        PATIENT as patient_id\n        , ENCOUNTER as encounter_id\n\n        -- timestamp\n        , cast(DATE as timestamp) as procedure_at\n\n        -- procedure details\n        , CODE as procedure_code\n        , DESCRIPTION as procedure_description\n        , BASE_COST as base_cost\n\n        -- reason for procedure\n        , REASONCODE as reason_code\n        , REASONDESCRIPTION as reason_description\n    from source\n),\n\nwith_surrogate_key as (\n    select\n        -- surrogate primary key (no natural key exists)\n        {{ dbt_utils.generate_surrogate_key(['patient_id', 'encounter_id', 'procedure_code', 'procedure_at']) }} as procedure_id\n        , *\n    from renamed\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from with_surrogate_key\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"stg_synthea__providers","path":"models/staging/synthea/stg_synthea__providers.sql","description":"Staging model for healthcare providers (doctors, nurses, etc.). One row per provider with specialization and affiliated organization.\n","dag":{"nodes":[{"id":"source","role":"import"},{"id":"renamed","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"stg_synthea__providers.sql","role":"final"}],"edges":[{"from":"source","to":"renamed","edge_type":"from"},{"from":"renamed","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","final":"final as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from renamed\n)","renamed":"renamed as (\n    select\n        -- primary key\n        Id as provider_id\n\n        -- foreign key\n        , ORGANIZATION as organization_id\n\n        -- attributes\n        , NAME as provider_name\n        , GENDER as gender\n        , SPECIALITY as specialty\n\n        -- location\n        , ADDRESS as address\n        , CITY as city\n        , STATE as state\n        , ZIP as zip_code\n        , LAT as latitude\n        , LON as longitude\n\n        -- metrics\n        , UTILIZATION as utilization\n    from source\n)","source":"source as (\n    select * from \"memory\".\"main\".\"providers\"\n)"},"raw_sql":"with source as (\n    select * from {{ source('synthea_raw', 'providers') }}\n),\n\nrenamed as (\n    select\n        -- primary key\n        Id as provider_id\n\n        -- foreign key\n        , ORGANIZATION as organization_id\n\n        -- attributes\n        , NAME as provider_name\n        , GENDER as gender\n        , SPECIALITY as specialty\n\n        -- location\n        , ADDRESS as address\n        , CITY as city\n        , STATE as state\n        , ZIP as zip_code\n        , LAT as latitude\n        , LON as longitude\n\n        -- metrics\n        , UTILIZATION as utilization\n    from source\n),\n\nfinal as (\n    select\n        *\n        , current_timestamp as _loaded_at\n    from renamed\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"v_encounter_summary","path":"models/marts/analytics/views/v_encounter_summary.sql","description":"Enriched encounter view with dimension attributes for ad-hoc analysis.\nEphemeral (not persisted) - used as a building block for other queries.\nJoins encounters with patient, provider, organization, and payer details.\n\nUse cases:\n- Ad-hoc encounter analysis\n- Building block for custom reports\n- Quick encounter lookups with full context\n","dag":{"nodes":[{"id":"encounters","role":"import"},{"id":"patients","role":"import"},{"id":"providers","role":"import"},{"id":"organizations","role":"import"},{"id":"payers","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"v_encounter_summary.sql","role":"final"}],"edges":[{"from":"encounters","to":"final","edge_type":"from"},{"from":"patients","to":"final","edge_type":"left"},{"from":"providers","to":"final","edge_type":"left"},{"from":"organizations","to":"final","edge_type":"left"},{"from":"payers","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","encounters":"encounters as (\n    select\n        encounter_key\n        , encounter_id\n        , patient_key\n        , patient_id\n        , provider_key\n        , provider_id\n        , organization_key\n        , organization_id\n        , payer_key\n        , payer_id\n        , encounter_start_at\n        , encounter_class\n        , encounter_description\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , duration_minutes\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n)","final":"final as (\n    select\n        -- identifiers\n        e.encounter_id\n        , cast(e.encounter_start_at as date) as encounter_date\n\n        -- patient\n        , e.patient_id\n        , coalesce(p.patient_name, 'Unknown Patient') as patient_name\n\n        -- provider\n        , e.provider_id\n        , coalesce(pr.provider_name, 'Unknown Provider') as provider_name\n\n        -- organization\n        , e.organization_id\n        , coalesce(o.organization_name, 'Unknown Organization') as organization_name\n\n        -- payer\n        , e.payer_id\n        , coalesce(py.payer_name, 'Unknown Payer') as payer_name\n\n        -- encounter details\n        , e.encounter_class\n        , e.encounter_description\n        , e.duration_minutes\n\n        -- costs\n        , coalesce(e.total_claim_cost, 0) as total_cost\n        , coalesce(e.payer_coverage, 0) as payer_coverage\n        , coalesce(e.patient_responsibility, 0) as patient_responsibility\n\n    from encounters as e\n    left join patients as p on e.patient_key = p.patient_key\n    left join providers as pr on e.provider_key = pr.provider_key\n    left join organizations as o on e.organization_key = o.organization_key\n    left join payers as py on e.payer_key = py.payer_key\n)","organizations":"organizations as (\n    select\n        organization_key\n        , organization_name\n    from \"memory\".\"main_marts\".\"dim_organizations\"\n)","patients":"patients as (\n    select\n        patient_key\n        , full_name as patient_name\n    from \"memory\".\"main_marts\".\"dim_patients\"\n    where is_current = true\n)","payers":"payers as (\n    select\n        payer_key\n        , payer_name\n    from \"memory\".\"main_marts\".\"dim_payers\"\n)","providers":"providers as (\n    select\n        provider_key\n        , provider_name\n    from \"memory\".\"main_marts\".\"dim_providers\"\n)"},"raw_sql":"{{\n    config(\n        materialized='ephemeral',\n        tags=['analytics', 'marts', 'view']\n    )\n}}\n\n{#\n    Encounter Summary View (Ephemeral)\n\n    Purpose: Enriched encounter view with dimension attributes\n    Materialization: Ephemeral (not persisted) - used as a building block\n    Use cases: Ad-hoc queries, building blocks for other models, BI tool queries\n\n    Joins fct_encounters with all dimension tables to provide a denormalized\n    view with human-readable names instead of just keys.\n#}\n\nwith encounters as (\n    select\n        encounter_key\n        , encounter_id\n        , patient_key\n        , patient_id\n        , provider_key\n        , provider_id\n        , organization_key\n        , organization_id\n        , payer_key\n        , payer_id\n        , encounter_start_at\n        , encounter_class\n        , encounter_description\n        , total_claim_cost\n        , payer_coverage\n        , patient_responsibility\n        , duration_minutes\n    from {{ ref('fct_encounters') }}\n),\n\npatients as (\n    select\n        patient_key\n        , full_name as patient_name\n    from {{ ref('dim_patients') }}\n    where is_current = true\n),\n\nproviders as (\n    select\n        provider_key\n        , provider_name\n    from {{ ref('dim_providers') }}\n),\n\norganizations as (\n    select\n        organization_key\n        , organization_name\n    from {{ ref('dim_organizations') }}\n),\n\npayers as (\n    select\n        payer_key\n        , payer_name\n    from {{ ref('dim_payers') }}\n),\n\nfinal as (\n    select\n        -- identifiers\n        e.encounter_id\n        , cast(e.encounter_start_at as date) as encounter_date\n\n        -- patient\n        , e.patient_id\n        , coalesce(p.patient_name, 'Unknown Patient') as patient_name\n\n        -- provider\n        , e.provider_id\n        , coalesce(pr.provider_name, 'Unknown Provider') as provider_name\n\n        -- organization\n        , e.organization_id\n        , coalesce(o.organization_name, 'Unknown Organization') as organization_name\n\n        -- payer\n        , e.payer_id\n        , coalesce(py.payer_name, 'Unknown Payer') as payer_name\n\n        -- encounter details\n        , e.encounter_class\n        , e.encounter_description\n        , e.duration_minutes\n\n        -- costs\n        , coalesce(e.total_claim_cost, 0) as total_cost\n        , coalesce(e.payer_coverage, 0) as payer_coverage\n        , coalesce(e.patient_responsibility, 0) as patient_responsibility\n\n    from encounters as e\n    left join patients as p on e.patient_key = p.patient_key\n    left join providers as pr on e.provider_key = pr.provider_key\n    left join organizations as o on e.organization_key = o.organization_key\n    left join payers as py on e.payer_key = py.payer_key\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"v_patient_current_conditions","path":"models/marts/analytics/views/v_patient_current_conditions.sql","description":"Current (active) conditions for each patient, filtered from fct_condition_cohorts.\nUse for patient panels, disease management dashboards, and care gap identification.\nGrain: (patient_id, condition_code) - only active conditions\n\nUse cases:\n- Patient panel management\n- Active disease registries\n- Care gap identification\n- Real-time patient condition views\n","dag":{"nodes":[{"id":"condition_cohorts","role":"import"},{"id":"final","role":"transform"},{"id":"(final select)","label":"v_patient_current_conditions.sql","role":"final"}],"edges":[{"from":"condition_cohorts","to":"final","edge_type":"from"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","condition_cohorts":"condition_cohorts as (\n    select\n        patient_key\n        , patient_id\n        , condition_key\n        , condition_code\n        , condition_description\n        , first_diagnosis_date\n        , months_with_condition\n        , encounter_count\n        , is_active\n    from \"memory\".\"main_marts\".\"fct_condition_cohorts\"\n    where is_active = true\n)","final":"final as (\n    select\n        patient_key\n        , patient_id\n        , condition_key\n        , condition_code\n        , condition_description\n        , first_diagnosis_date\n        , months_with_condition\n        , encounter_count\n    from condition_cohorts\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        tags=['analytics', 'marts', 'view']\n    )\n}}\n\n{#\n    Patient Current Conditions View\n\n    Purpose: Current (active) conditions for each patient\n    Grain: One row per patient-condition combination where condition is active\n    Use cases: Patient panels, disease management dashboards, care gap analysis\n\n    Filters fct_condition_cohorts to only active conditions (no end date).\n#}\n\nwith condition_cohorts as (\n    select\n        patient_key\n        , patient_id\n        , condition_key\n        , condition_code\n        , condition_description\n        , first_diagnosis_date\n        , months_with_condition\n        , encounter_count\n        , is_active\n    from {{ ref('fct_condition_cohorts') }}\n    where is_active = true\n),\n\nfinal as (\n    select\n        patient_key\n        , patient_id\n        , condition_key\n        , condition_code\n        , condition_description\n        , first_diagnosis_date\n        , months_with_condition\n        , encounter_count\n    from condition_cohorts\n)\n\nselect * from final","tests":[],"is_recursive":false},{"name":"v_provider_active_patients","path":"models/marts/analytics/views/v_provider_active_patients.sql","description":"Active patient count per provider for panel management and workload analysis.\nAggregates patients with active conditions by their treating provider.\nGrain: provider_id\n\nUse cases:\n- Provider panel size management\n- Workload distribution analysis\n- Capacity planning\n- Provider assignment optimization\n","dag":{"nodes":[{"id":"providers","role":"import"},{"id":"current_conditions","role":"import"},{"id":"patient_recent_encounters","role":"import"},{"id":"patient_provider_assignment","role":"transform"},{"id":"active_conditions_by_provider","role":"transform"},{"id":"provider_summary","role":"transform"},{"id":"final","role":"transform"},{"id":"(final select)","label":"v_provider_active_patients.sql","role":"final"}],"edges":[{"from":"patient_recent_encounters","to":"patient_provider_assignment","edge_type":"from"},{"from":"current_conditions","to":"active_conditions_by_provider","edge_type":"from"},{"from":"patient_provider_assignment","to":"active_conditions_by_provider","edge_type":"inner"},{"from":"active_conditions_by_provider","to":"provider_summary","edge_type":"from"},{"from":"providers","to":"final","edge_type":"from"},{"from":"provider_summary","to":"final","edge_type":"left"},{"from":"final","to":"(final select)","edge_type":"from"}]},"compiled_sql":{"(final select)":"select * from final","active_conditions_by_provider":"active_conditions_by_provider as (\n    select\n        ppa.provider_key\n        , ppa.provider_id\n        , cc.patient_id\n        , cc.condition_key\n    from current_conditions as cc\n    inner join patient_provider_assignment as ppa\n        on cc.patient_id = ppa.patient_id\n)","current_conditions":"current_conditions as (\n    select\n        cc.patient_key\n        , cc.patient_id\n        , cc.condition_key\n        , cc.condition_code\n    from \"memory\".\"main_marts\".\"fct_condition_cohorts\" as cc\n    where cc.is_active = true\n)","final":"final as (\n    select\n        p.provider_key\n        , p.provider_id\n        , p.provider_name\n        , p.organization_key\n        , p.organization_id\n        , coalesce(ps.active_patient_count, 0) as active_patient_count\n        , coalesce(ps.total_active_conditions, 0) as total_active_conditions\n        , case\n            when coalesce(ps.active_patient_count, 0) > 0\n            then round(\n                cast(ps.total_active_conditions as decimal) / ps.active_patient_count,\n                2\n            )\n            else 0\n        end as avg_conditions_per_patient\n    from providers as p\n    left join provider_summary as ps\n        on p.provider_key = ps.provider_key\n)","patient_provider_assignment":"patient_provider_assignment as (\n    select\n        patient_id\n        , provider_key\n        , provider_id\n    from patient_recent_encounters\n    where rn = 1\n)","patient_recent_encounters":"patient_recent_encounters as (\n    select\n        patient_id\n        , provider_key\n        , provider_id\n        , row_number() over (\n            partition by patient_id\n            order by encounter_start_at desc\n        ) as rn\n    from \"memory\".\"main_marts\".\"fct_encounters\"\n    where provider_key != -1\n)","provider_summary":"provider_summary as (\n    select\n        provider_key\n        , provider_id\n        , count(distinct patient_id) as active_patient_count\n        , count(*) as total_active_conditions\n    from active_conditions_by_provider\n    group by provider_key, provider_id\n)","providers":"providers as (\n    select\n        provider_key\n        , provider_id\n        , provider_name\n        , organization_key\n        , organization_id\n    from \"memory\".\"main_marts\".\"dim_providers\"\n    where provider_key != -1\n)"},"raw_sql":"{{\n    config(\n        materialized='table',\n        tags=['analytics', 'marts', 'view']\n    )\n}}\n\n{#\n    Provider Active Patients View\n\n    Purpose: Active patient count per provider for panel management\n    Grain: One row per provider\n    Use cases: Provider workload analysis, panel management, capacity planning\n\n    Aggregates patients with active conditions by their most recent provider.\n    A patient is attributed to the provider who saw them most recently for an active condition.\n#}\n\nwith providers as (\n    select\n        provider_key\n        , provider_id\n        , provider_name\n        , organization_key\n        , organization_id\n    from {{ ref('dim_providers') }}\n    where provider_key != -1\n),\n\n-- get current conditions with their most recent encounter\ncurrent_conditions as (\n    select\n        cc.patient_key\n        , cc.patient_id\n        , cc.condition_key\n        , cc.condition_code\n    from {{ ref('fct_condition_cohorts') }} as cc\n    where cc.is_active = true\n),\n\n-- get the most recent encounter per patient to determine their provider\npatient_recent_encounters as (\n    select\n        patient_id\n        , provider_key\n        , provider_id\n        , row_number() over (\n            partition by patient_id\n            order by encounter_start_at desc\n        ) as rn\n    from {{ ref('fct_encounters') }}\n    where provider_key != -1\n),\n\n-- assign patients to their most recent provider\npatient_provider_assignment as (\n    select\n        patient_id\n        , provider_key\n        , provider_id\n    from patient_recent_encounters\n    where rn = 1\n),\n\n-- join active conditions to provider assignments\nactive_conditions_by_provider as (\n    select\n        ppa.provider_key\n        , ppa.provider_id\n        , cc.patient_id\n        , cc.condition_key\n    from current_conditions as cc\n    inner join patient_provider_assignment as ppa\n        on cc.patient_id = ppa.patient_id\n),\n\n-- aggregate by provider\nprovider_summary as (\n    select\n        provider_key\n        , provider_id\n        , count(distinct patient_id) as active_patient_count\n        , count(*) as total_active_conditions\n    from active_conditions_by_provider\n    group by provider_key, provider_id\n),\n\nfinal as (\n    select\n        p.provider_key\n        , p.provider_id\n        , p.provider_name\n        , p.organization_key\n        , p.organization_id\n        , coalesce(ps.active_patient_count, 0) as active_patient_count\n        , coalesce(ps.total_active_conditions, 0) as total_active_conditions\n        , case\n            when coalesce(ps.active_patient_count, 0) > 0\n            then round(\n                cast(ps.total_active_conditions as decimal) / ps.active_patient_count,\n                2\n            )\n            else 0\n        end as avg_conditions_per_patient\n    from providers as p\n    left join provider_summary as ps\n        on p.provider_key = ps.provider_key\n)\n\nselect * from final","tests":[],"is_recursive":false}],"manifest_nodes":{"dim_conditions":{"description":"Master condition dimension for healthcare analytics.\nOne row per unique ICD/SNOMED condition code, deduplicated from staging.\nUse for filtering and grouping by condition across fact tables.\n\nUse cases:\n- Condition-based cohort analysis\n- Disease prevalence tracking\n- Condition frequency and distribution reporting\n- Join target for condition-related facts\n","materialized":"table","tags":["analytics","marts","dimension"],"columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"condition_code","description":"ICD/SNOMED code (natural key)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"condition_description","description":"Full condition name/description","tests":[{"name":"not null"}]},{"name":"condition_key","description":"Surrogate key (row_number)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"encounter_count","description":"Total number of encounters with this condition","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"first_occurrence_date","description":"Earliest date this condition was diagnosed in the dataset"},{"name":"last_occurrence_date","description":"Most recent date this condition was diagnosed"},{"name":"patient_count","description":"Number of unique patients with this condition","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]}]},"dim_date":{"description":"Calendar dimension covering 1909-01-01 to 2025-12-31. Provides date attributes, day/week/month/quarter/year hierarchies, weekend flags, and US holiday identification.\n","materialized":"table","columns":[{"name":"date_actual","description":"The actual date value","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"},{"name":"unique"}]},{"name":"date_key","description":"Surrogate key in YYYYMMDD integer format (e.g., 20240115)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"},{"name":"unique"}]},{"name":"day_name","description":"Full day name (e.g., Monday, Tuesday)","tests":[{"name":"not null"}]},{"name":"day_name_short","description":"Abbreviated day name (e.g., Mon, Tue)","tests":[{"name":"not null"}]},{"name":"day_of_month","description":"Day of the month (1-31)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"day_of_week","description":"Day of week number (US convention - Sunday=1, Saturday=7)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"day_of_year","description":"Day of the year (1-366)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"holiday_name","description":"Name of the US holiday (null if not a holiday)"},{"name":"is_us_holiday","description":"Boolean flag indicating if date is a recognized US holiday","tests":[{"name":"accepted values","values":["true","false"]},{"name":"not null"}]},{"name":"is_weekend","description":"Boolean flag indicating if date falls on Saturday or Sunday","tests":[{"name":"accepted values","values":["true","false"]},{"name":"not null"}]},{"name":"month_actual","description":"Month number (1-12)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"month_name","description":"Full month name (e.g., January, February)","tests":[{"name":"not null"}]},{"name":"month_name_short","description":"Abbreviated month name (e.g., Jan, Feb)","tests":[{"name":"not null"}]},{"name":"quarter_actual","description":"Quarter number (1-4)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"quarter_name","description":"Quarter name (Q1, Q2, Q3, Q4)","tests":[{"name":"accepted values","values":["Q1","Q2","Q3","Q4"]},{"name":"not null"}]},{"name":"week_of_year","description":"Week of the year (1-53)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"year_actual","description":"Year number","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"dim_organizations":{"description":"Organization dimension containing healthcare facilities. Includes an unknown member row (organization_key = -1) for handling missing lookups.\n","materialized":"table","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"address","description":"Street address"},{"name":"city","description":"City"},{"name":"latitude","description":"Latitude coordinate"},{"name":"longitude","description":"Longitude coordinate"},{"name":"organization_id","description":"Natural organization identifier (UUID)","tests":[{"name":"not null"}]},{"name":"organization_key","description":"Surrogate key (-1 for unknown member)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"organization_name","description":"Name of the healthcare organization","tests":[{"name":"not null"}]},{"name":"phone","description":"Phone number"},{"name":"revenue","description":"Total revenue","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"state","description":"State (full state name)"},{"name":"utilization","description":"Total utilization count","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"zip_code","description":"ZIP code"}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"dim_patients":{"description":"Patient dimension with SCD Type 2 history tracking. Each row represents a specific version of a patient's record. Includes an unknown member row (patient_key = -1) for handling missing lookups.\nSCD Type 2 columns: patient_key (surrogate), patient_id (natural), valid_from, valid_to, is_current.\n","materialized":"table","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"address","description":"Street address"},{"name":"age_years","description":"Current age or age at death (in years)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"birth_date","description":"Patient date of birth","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"city","description":"City of residence"},{"name":"county","description":"County of residence"},{"name":"death_date","description":"Patient date of death (null if alive)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"ethnicity","description":"Patient ethnicity (hispanic or nonhispanic)"},{"name":"first_name","description":"Patient's first name","tests":[{"name":"not null"}]},{"name":"full_name","description":"Patient's full name (first + last)","tests":[{"name":"not null"}]},{"name":"gender","description":"Patient gender (M or F)","tests":[{"name":"accepted values","values":["M","F"]}]},{"name":"healthcare_coverage","description":"Total healthcare coverage received","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"healthcare_expenses","description":"Total healthcare expenses incurred","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"is_current","description":"Boolean flag indicating if this is the current version","tests":[{"name":"accepted values","values":["true","false"]},{"name":"not null"}]},{"name":"is_deceased","description":"Boolean flag indicating if patient has died","tests":[{"name":"accepted values","values":["true","false"]},{"name":"not null"}]},{"name":"last_name","description":"Patient's last name","tests":[{"name":"not null"}]},{"name":"latitude","description":"Latitude coordinate of residence"},{"name":"longitude","description":"Longitude coordinate of residence"},{"name":"marital_status","description":"Marital status (M=Married, S=Single, or blank)"},{"name":"name_prefix","description":"Name prefix (Mr., Mrs., Ms., etc.)"},{"name":"name_suffix","description":"Name suffix (Jr., Sr., III, etc.)"},{"name":"patient_id","description":"Natural patient identifier (UUID), same across SCD2 versions","tests":[{"name":"not null"}]},{"name":"patient_key","description":"Surrogate key (unique per version, -1 for unknown member)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"race","description":"Patient race"},{"name":"state","description":"State of residence (full state name)"},{"name":"valid_from","description":"Date when this SCD2 version became active","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"valid_to","description":"Date when this SCD2 version was superseded (null = current)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"zip_code","description":"ZIP code"}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"dim_payers":{"description":"Payer dimension containing insurance payers. Includes an unknown member row (payer_key = -1) for handling missing lookups.\n","materialized":"table","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"address","description":"Street address"},{"name":"amount_covered","description":"Total amount covered by payer","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"amount_uncovered","description":"Total amount not covered by payer"},{"name":"average_quality_of_life_score","description":"Average quality of life score for members"},{"name":"city","description":"City"},{"name":"coverage_rate","description":"Derived coverage rate (amount_covered / total amount)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"covered_encounters","description":"Number of encounters covered"},{"name":"covered_immunizations","description":"Number of immunizations covered"},{"name":"covered_medications","description":"Number of medications covered"},{"name":"covered_procedures","description":"Number of procedures covered"},{"name":"member_months","description":"Total member months"},{"name":"payer_id","description":"Natural payer identifier (UUID)","tests":[{"name":"not null"}]},{"name":"payer_key","description":"Surrogate key (-1 for unknown member)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"payer_name","description":"Name of the insurance payer","tests":[{"name":"not null"}]},{"name":"phone","description":"Phone number"},{"name":"revenue","description":"Total revenue collected","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"state","description":"State"},{"name":"uncovered_encounters","description":"Number of encounters not covered"},{"name":"uncovered_immunizations","description":"Number of immunizations not covered"},{"name":"uncovered_medications","description":"Number of medications not covered"},{"name":"uncovered_procedures","description":"Number of procedures not covered"},{"name":"unique_customers","description":"Number of unique customers"},{"name":"zip_code","description":"ZIP code"}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"dim_providers":{"description":"Provider dimension containing healthcare providers (doctors, nurses, etc.). Includes an unknown member row (provider_key = -1) for handling missing lookups.\n","materialized":"table","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"address","description":"Street address"},{"name":"city","description":"City"},{"name":"gender","description":"Provider gender (M or F)","tests":[{"name":"accepted values","values":["M","F"]}]},{"name":"latitude","description":"Latitude coordinate"},{"name":"longitude","description":"Longitude coordinate"},{"name":"organization_id","description":"Natural organization identifier","tests":[{"name":"not null"}]},{"name":"organization_key","description":"Foreign key to dim_organizations (-1 for unknown)","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_organizations.organization_key"}]},{"name":"provider_id","description":"Natural provider identifier (UUID)","tests":[{"name":"not null"}]},{"name":"provider_key","description":"Surrogate key (-1 for unknown member)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"provider_name","description":"Full name of the provider","tests":[{"name":"not null"}]},{"name":"specialty","description":"Medical specialty"},{"name":"state","description":"State (full state name)"},{"name":"utilization","description":"Total utilization count","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"zip_code","description":"ZIP code"}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"fct_clinical_events":{"description":"Unified clinical events fact table combining conditions, medications, and procedures. Each row represents a single clinical event with standardized structure. Links to patient and encounter dimensions.\n","materialized":"table","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"clinical_event_key","description":"Surrogate key for the clinical event","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"code","description":"Clinical code (SNOMED-CT or RxNorm)","tests":[{"name":"not null"}]},{"name":"code_system","description":"Code system (SNOMED-CT or RXNORM)","tests":[{"name":"accepted values","values":["SNOMED-CT","RXNORM"]},{"name":"not null"}]},{"name":"description","description":"Description of the clinical event","tests":[{"name":"not null"}]},{"name":"encounter_id","description":"Natural encounter identifier","tests":[{"name":"not null"}]},{"name":"encounter_key","description":"Foreign key to fct_encounters (-1 for unknown)","tests":[{"name":"not null"},{"name":"relationships","detail":"fct_encounters.encounter_key"}]},{"name":"event_cost","description":"Cost of the clinical event","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"event_date_key","description":"Foreign key to dim_date for event start","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_date.date_key"}]},{"name":"event_end_date","description":"End date of the clinical event (null if ongoing or one-time)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"event_id","description":"Natural event identifier (condition_id, medication_id, or procedure_id)","tests":[{"name":"not null"}]},{"name":"event_start_date","description":"Start date of the clinical event","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"event_type","description":"Type of clinical event (CONDITION, MEDICATION, PROCEDURE)","tests":[{"name":"accepted values","values":["CONDITION","MEDICATION","PROCEDURE"]},{"name":"not null"}]},{"name":"patient_id","description":"Natural patient identifier","tests":[{"name":"not null"}]},{"name":"patient_key","description":"Foreign key to dim_patients (-1 for unknown)","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_patients.patient_key"}]},{"name":"reason_code","description":"Clinical code for the reason of the event"},{"name":"reason_description","description":"Description of the reason for the event"}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"fct_condition_cohorts":{"description":"Patient-condition cohort analysis for disease management and population health.\nOne row per unique patient-condition combination with timeline and encounter details.\nGrain: (patient_id, condition_code)\n\nUse cases:\n- Disease management program enrollment\n- Cohort identification for clinical trials\n- Chronic condition tracking\n- Care gap analysis\n- Risk stratification by condition\n","materialized":"table","tags":["analytics","marts","fact"],"columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"condition_code","description":"ICD/SNOMED condition code","tests":[{"name":"not null"}]},{"name":"condition_cohort_key","description":"Surrogate key (MD5 hash of patient_id + condition_code)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"condition_description","description":"Full condition name"},{"name":"condition_key","description":"Foreign key to dim_conditions","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_conditions.condition_key"}]},{"name":"encounter_count","description":"Number of encounters with this condition","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"first_diagnosis_date","description":"Date of first diagnosis","tests":[{"name":"not null"}]},{"name":"first_diagnosis_year","description":"Year of first diagnosis","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"is_active","description":"True if condition has no end date (currently active)","tests":[{"name":"accepted values","values":["true","false"]},{"name":"not null"}]},{"name":"last_diagnosis_date","description":"Date of most recent diagnosis (null if first occurrence only)"},{"name":"months_with_condition","description":"Months between first and last diagnosis (0 if single occurrence)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"patient_id","description":"Natural patient identifier","tests":[{"name":"not null"}]},{"name":"patient_key","description":"Foreign key to dim_patients","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_patients.patient_key"}]}],"model_tests":[{"name":"dbt_utils.unique_combination_of_columns"}]},"fct_cost_analysis":{"description":"Detailed cost breakdown for financial analysis and revenue cycle management.\nOne row per encounter with cost allocation details across payer and patient.\nGrain: encounter_id\n\nUse cases:\n- Financial performance reporting\n- Payer mix analysis\n- Patient out-of-pocket tracking\n- Cost driver identification\n- Revenue cycle optimization\n","materialized":"table","tags":["analytics","marts","fact"],"columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"cost_analysis_key","description":"Surrogate key (MD5 hash of encounter_id)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"cost_per_procedure","description":"Average cost per procedure (null if no procedures)"},{"name":"coverage_pct","description":"Percentage covered by insurance (0-100)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_class","description":"Type of encounter (ambulatory, wellness, etc.)"},{"name":"encounter_date","description":"Date of the encounter"},{"name":"encounter_date_key","description":"Foreign key to dim_date"},{"name":"encounter_id","description":"Natural encounter identifier","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"encounter_key","description":"Foreign key to fct_encounters","tests":[{"name":"not null"},{"name":"relationships","detail":"fct_encounters.encounter_key"}]},{"name":"patient_cost_pct","description":"Percentage owed by patient (0-100)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"patient_id","description":"Natural patient identifier"},{"name":"patient_key","description":"Foreign key to dim_patients"},{"name":"patient_responsibility","description":"Amount owed by patient","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"payer_coverage","description":"Amount covered by insurance","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"payer_id","description":"Natural payer identifier"},{"name":"payer_key","description":"Foreign key to dim_payers","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_payers.payer_key"}]},{"name":"procedure_count","description":"Number of procedures in the encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"provider_id","description":"Natural provider identifier"},{"name":"provider_key","description":"Foreign key to dim_providers","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_providers.provider_key"}]},{"name":"total_cost","description":"Total claim cost","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"year_actual","description":"Calendar year of encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]}]},"fct_encounters":{"description":"Encounter fact table containing healthcare visits/encounters. Links to patient, provider, organization, and payer dimensions. Includes date keys, costs, and derived duration.\n","materialized":"table","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"base_encounter_cost","description":"Base cost of the encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"duration_minutes","description":"Duration of encounter in minutes","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_class","description":"Type of encounter (ambulatory, wellness, emergency, etc.)","tests":[{"name":"accepted values","values":["ambulatory","wellness","emergency","urgentcare","outpatient","inpatient"]},{"name":"not null"}]},{"name":"encounter_code","description":"SNOMED CT code for the encounter type"},{"name":"encounter_description","description":"Description of the encounter type"},{"name":"encounter_end_at","description":"End timestamp of the encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_end_date_key","description":"Foreign key to dim_date for encounter end"},{"name":"encounter_id","description":"Natural encounter identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"encounter_key","description":"Surrogate key for the encounter","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"encounter_start_at","description":"Start timestamp of the encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"encounter_start_date_key","description":"Foreign key to dim_date for encounter start","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_date.date_key"}]},{"name":"organization_id","description":"Natural organization identifier","tests":[{"name":"not null"}]},{"name":"organization_key","description":"Foreign key to dim_organizations (-1 for unknown)","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_organizations.organization_key"}]},{"name":"patient_age_at_encounter","description":"Patient's age at the time of the encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"patient_id","description":"Natural patient identifier","tests":[{"name":"not null"}]},{"name":"patient_key","description":"Foreign key to dim_patients (-1 for unknown)","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_patients.patient_key"}]},{"name":"patient_responsibility","description":"Amount patient is responsible for (total_claim_cost - payer_coverage)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"payer_coverage","description":"Amount covered by payer","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"payer_id","description":"Natural payer identifier","tests":[{"name":"not null"}]},{"name":"payer_key","description":"Foreign key to dim_payers (-1 for unknown)","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_payers.payer_key"}]},{"name":"provider_id","description":"Natural provider identifier","tests":[{"name":"not null"}]},{"name":"provider_key","description":"Foreign key to dim_providers (-1 for unknown)","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_providers.provider_key"}]},{"name":"reason_code","description":"SNOMED CT code for the reason of visit"},{"name":"reason_description","description":"Description of the reason for visit"},{"name":"total_claim_cost","description":"Total claim cost","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"fct_encounters_incremental":{"description":"Incremental fact table of encounter events. Appends encounters newer than the latest already-loaded start_time via an is_incremental() filter.","materialized":"incremental","columns":[{"name":"encounter_id","description":"Natural key of the encounter (unique per visit)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"encounter_type","description":"Visit class (wellness, emergency, ...)"},{"name":"patient_id","description":"Patient the encounter belongs to"},{"name":"start_time","description":"Encounter start timestamp - the incremental high-water mark"},{"name":"total_cost","description":"Total claim cost for the encounter"}]},"fct_encounters_monthly":{"description":"Monthly aggregated encounter statistics by encounter class. Provides counts, costs, and patient metrics grouped by year-month and encounter type.\n","materialized":"table","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"avg_duration_minutes","description":"Average encounter duration in minutes","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_class","description":"Type of encounter","tests":[{"name":"accepted values","values":["ambulatory","wellness","emergency","urgentcare","outpatient","inpatient"]},{"name":"not null"}]},{"name":"encounter_count","description":"Number of encounters in the month","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"month_actual","description":"Month number (1-12)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"total_claim_cost","description":"Sum of total claim costs","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"total_patient_responsibility","description":"Sum of patient responsibility amounts","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"total_payer_coverage","description":"Sum of payer coverage amounts","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"unique_patients","description":"Number of unique patients with encounters","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"year_actual","description":"Year number","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"year_month","description":"Year-month string (YYYY-MM format)","tests":[{"name":"dbt_expectations.expect_column_values_to_match_regex"},{"name":"not null"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"fct_encounters_yearly":{"description":"Yearly aggregated encounter statistics by encounter class. Provides counts, costs, patient metrics, and encounters per patient ratio.\n","materialized":"table","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"avg_duration_minutes","description":"Average encounter duration in minutes","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_class","description":"Type of encounter","tests":[{"name":"accepted values","values":["ambulatory","wellness","emergency","urgentcare","outpatient","inpatient"]},{"name":"not null"}]},{"name":"encounter_count","description":"Number of encounters in the year","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"encounters_per_patient","description":"Average number of encounters per patient","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"total_claim_cost","description":"Sum of total claim costs","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"total_patient_responsibility","description":"Sum of patient responsibility amounts","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"total_payer_coverage","description":"Sum of payer coverage amounts","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"unique_patients","description":"Number of unique patients with encounters","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"year_actual","description":"Year number","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"fct_patient_summary":{"description":"Annual patient-level aggregations for outcomes tracking and population health analysis.\nOne row per patient per calendar year with comprehensive utilization and cost metrics.\nGrain: (patient_id, year_actual)\n\nUse cases:\n- Patient outcomes tracking over time\n- Annual cost summaries and trends\n- Cohort analysis and patient stratification\n- Health trajectory visualization\n- High-cost patient identification\n","materialized":"table","tags":["analytics","marts","fact"],"columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"condition_count","description":"Number of distinct conditions diagnosed in the year","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_count","description":"Number of encounters in the year","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"patient_age_at_year_end","description":"Patient age as of December 31 of the year","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"patient_id","description":"Natural patient identifier","tests":[{"name":"not null"}]},{"name":"patient_key","description":"Foreign key to dim_patients","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_patients.patient_key"}]},{"name":"patient_responsibility","description":"Amount owed by patient (copay + coinsurance)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"patient_summary_key","description":"Surrogate key (MD5 hash of patient_id + year_actual)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"payer_coverage","description":"Amount covered by insurance","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"payer_coverage_pct","description":"Percentage of costs covered by insurance (0-100)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"procedure_count","description":"Number of procedures in the year","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"total_cost","description":"Total claim cost for the year","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"unique_organizations","description":"Number of distinct organizations visited","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"unique_providers","description":"Number of distinct providers seen","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"year_actual","description":"Calendar year of the summary","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]}],"model_tests":[{"name":"dbt_utils.unique_combination_of_columns"}]},"fct_provider_metrics":{"description":"Monthly provider-level utilization and performance metrics.\nOne row per provider per calendar month with patient volumes, costs, and efficiency metrics.\nGrain: (provider_id, year_actual, month_actual)\n\nUse cases:\n- Provider performance tracking\n- Workload distribution analysis\n- Cost efficiency comparisons\n- Capacity planning and staffing\n- Quality improvement initiatives\n","materialized":"table","tags":["analytics","marts","fact"],"columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded"},{"name":"avg_cost_per_encounter","description":"Average cost per encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"avg_encounter_duration_minutes","description":"Average encounter duration in minutes","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"avg_patient_age","description":"Average age of patients seen","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_count","description":"Number of encounters in the month","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"encounters_per_patient_avg","description":"Average encounters per patient","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"month_actual","description":"Calendar month (1-12)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"organization_id","description":"Natural organization identifier"},{"name":"organization_key","description":"Foreign key to dim_organizations"},{"name":"provider_id","description":"Natural provider identifier","tests":[{"name":"not null"}]},{"name":"provider_key","description":"Foreign key to dim_providers","tests":[{"name":"not null"},{"name":"relationships","detail":"dim_providers.provider_key"}]},{"name":"provider_metrics_key","description":"Surrogate key (MD5 hash of provider_id + year_month_str)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"total_cost","description":"Total claim cost for the month","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"total_payer_coverage","description":"Amount covered by insurance","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"total_procedures","description":"Total procedures performed","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"unique_patient_count","description":"Number of distinct patients seen","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"year_actual","description":"Calendar year","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"year_month_str","description":"Year-month string (YYYY-MM)"}],"model_tests":[{"name":"dbt_utils.unique_combination_of_columns"}]},"int_dq_quarantine__encounters":{"description":"Encounters that failed data quality validations and are excluded from downstream marts.\n\nRecords are quarantined when any of the following validations fail:\n- valid_encounter_timestamps: encounter_end_at >= encounter_start_at\n- no_future_encounter_dates: encounter_start_at <= current_timestamp\n- end_after_1900: encounter_end_at >= timestamp '1900-01-01'\n- start_after_1900: encounter_start_at >= timestamp '1900-01-01'\n\nThis table preserves data quality violations for investigation without polluting fact tables.\n","materialized":"table","tags":["intermediate","quarantine","data_quality"],"columns":[{"name":"encounter_id","description":"Natural key for the encounter (from source system)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"end_after_1900","description":"Flag: encounter_end_at >= timestamp '1900-01-01'"},{"name":"failed_dq_tests","description":"Array of failed validation test names","tests":[{"name":"not null"}]},{"name":"is_dq_valid","description":"Data quality validity flag - should always be false in quarantine","tests":[{"name":"accepted values","values":["false"]},{"name":"not null"}]},{"name":"no_future_encounter_dates","description":"Flag: encounter_start_at <= current_timestamp"},{"name":"start_after_1900","description":"Flag: encounter_start_at >= timestamp '1900-01-01'"},{"name":"valid_encounter_timestamps","description":"Flag: encounter_end_at >= encounter_start_at"}]},"int_dq_quarantine__medications":{"description":"Medications that failed data quality validations and are excluded from downstream marts.\n\nRecords are quarantined when any of the following validations fail:\n- valid_medication_dates: medication_end_at is null or medication_end_at >= medication_start_at\n- no_future_medication_dates: cast(medication_start_at as date) <= current_date\n- start_after_1900: medication_start_at >= timestamp '1900-01-01'\n- end_after_1900_if_present: medication_end_at is null or medication_end_at >= timestamp '1900-01-01'\n\nThis table preserves data quality violations for investigation without polluting fact tables.\n","materialized":"table","tags":["intermediate","quarantine","data_quality"],"columns":[{"name":"end_after_1900_if_present","description":"Flag: medication_end_at is null or medication_end_at >= timestamp '1900-01-01'"},{"name":"failed_dq_tests","description":"Array of failed validation test names","tests":[{"name":"not null"}]},{"name":"is_dq_valid","description":"Data quality validity flag - should always be false in quarantine","tests":[{"name":"accepted values","values":["false"]},{"name":"not null"}]},{"name":"medication_id","description":"Surrogate key for the medication record","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"no_future_medication_dates","description":"Flag: cast(medication_start_at as date) <= current_date"},{"name":"start_after_1900","description":"Flag: medication_start_at >= timestamp '1900-01-01'"},{"name":"valid_medication_dates","description":"Flag: medication_end_at is null or medication_end_at >= medication_start_at"}]},"int_encounters__enriched":{"description":"Enriched encounter model that aggregates clinical event counts and costs per encounter. Joins conditions, medications, and procedures to provide a complete view of each encounter's clinical activity and associated costs.\n","materialized":"view","columns":[{"name":"condition_count","description":"Number of conditions diagnosed during this encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"encounter_id","description":"Unique encounter identifier (UUID), sourced from fct_encounters","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"medication_count","description":"Number of medications prescribed during this encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"procedure_count","description":"Number of procedures performed during this encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"total_condition_cost","description":"Total cost associated with conditions (currently always 0 per model logic)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"total_event_cost","description":"Total cost of all clinical events (conditions + medications + procedures). Note: Condition costs are currently set to 0 in the model.\n","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"total_event_count","description":"Total count of all clinical events (conditions + medications + procedures)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"total_medication_cost","description":"Total cost of medications prescribed during this encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"total_procedure_cost","description":"Total cost of procedures performed during this encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"int_patients__with_conditions":{"description":"Patient-level condition history with aggregated statistics and chronic disease flags. Provides counts of total and active conditions, condition date ranges, and boolean flags for common chronic conditions (diabetes, hypertension, heart disease).\nIMPORTANT: Chronic condition flags use simplified text matching on condition descriptions. This is for analytics/reporting only, not clinical decisions.\n","materialized":"view","columns":[{"name":"active_conditions","description":"Number of currently active conditions (no end date)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"chronic_condition_count","description":"Count of tracked chronic conditions (0-3, based on diabetes + hypertension + heart disease flags)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"first_condition_date","description":"Date of earliest condition diagnosis for this patient","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"has_diabetes","description":"Boolean flag indicating if patient has any diabetes-related condition","tests":[{"name":"accepted values","values":["true","false"]},{"name":"not null"}]},{"name":"has_heart_disease","description":"Boolean flag indicating if patient has any heart disease condition","tests":[{"name":"accepted values","values":["true","false"]},{"name":"not null"}]},{"name":"has_hypertension","description":"Boolean flag indicating if patient has hypertension or high blood pressure","tests":[{"name":"accepted values","values":["true","false"]},{"name":"not null"}]},{"name":"last_condition_date","description":"Date of most recent condition diagnosis for this patient","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"patient_id","description":"Unique patient identifier (UUID), sourced from current dim_patients records","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"total_conditions","description":"Total number of conditions ever diagnosed for this patient","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"mart_date_state_grid":{"description":"Dense month x state reporting scaffold.\nOne row per (calendar month x patient state) combination — the full\ncartesian product of dim_date months and the non-null states observed\nin patient staging. Left-join sparse activity facts against this grid\nso zero-activity cells render as explicit zeros.\nGrain: month_key x state\n\nUse cases:\n- Dense time-series dashboards (no missing month/state cells)\n- Zero-activity gap detection\n- cute-dbt cross-join CTE-edge demo (cute-dbt#64)\n","materialized":"table","tags":["analytics","reporting","marts"],"columns":[{"name":"month_actual","description":"Calendar month number (1-12) of the grid cell","tests":[{"name":"not null"}]},{"name":"month_key","description":"Month surrogate key in YYYYMM integer form (e.g., 202401)","tests":[{"name":"not null"}]},{"name":"month_name","description":"Full month name (e.g., January)"},{"name":"state","description":"Patient state, distinct and non-null from staging","tests":[{"name":"not null"}]},{"name":"year_actual","description":"Calendar year of the grid cell","tests":[{"name":"not null"}]}],"model_tests":[{"name":"dbt_utils.unique_combination_of_columns"}]},"mart_dq_summary":{"description":"Data quality summary metrics for monitoring quarantine rates and validation failures.\nOne row per entity type (encounters, medications) with quarantine counts and failure breakdowns.\nGrain: entity_type\n\nUse cases:\n- Data quality monitoring dashboards\n- Quarantine rate trending\n- Validation failure root cause analysis\n- Data quality SLA tracking\n","materialized":"table","tags":["analytics","data_quality","marts"],"columns":[{"name":"_generated_at","description":"Timestamp when summary was generated"},{"name":"entity_type","description":"Type of entity being measured (encounters, medications)","tests":[{"name":"accepted values","values":["encounters","medications"]},{"name":"not null"}]},{"name":"failed_future_date_validations","description":"Count of records with future dates"},{"name":"failed_historical_end_validations","description":"Count of records with end dates before 1900"},{"name":"failed_historical_start_validations","description":"Count of records with start dates before 1900"},{"name":"failed_timestamp_validations","description":"Count of records failing timestamp/date sequence validations"},{"name":"quarantine_rate_pct","description":"Percentage of records quarantined (quarantined_count / total_count * 100)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"quarantined_count","description":"Number of records failing data quality validations","tests":[{"name":"not null"}]},{"name":"total_count","description":"Total number of records (valid + quarantined)","tests":[{"name":"not null"}]}]},"stg_synthea__conditions":{"description":"Staging model for patient conditions/diagnoses. One row per condition instance with surrogate key.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"condition_code","description":"SNOMED CT code for the condition","tests":[{"name":"not null"}]},{"name":"condition_description","description":"Description of the condition","tests":[{"name":"not null"}]},{"name":"condition_end_date","description":"Date when condition resolved (null if ongoing)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"condition_id","description":"Surrogate key for the condition record","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"condition_start_date","description":"Date when condition was diagnosed","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"encounter_id","description":"Foreign key to the encounter","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__encounters.encounter_id"}]},{"name":"patient_id","description":"Foreign key to the patient","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__patients.patient_id"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"stg_synthea__encounters":{"description":"Staging model for healthcare encounters/visits. One row per encounter with patient, provider, organization, and payer relationships.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"base_encounter_cost","description":"Base cost of the encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_class","description":"Type of encounter (ambulatory, wellness, emergency, etc.)","tests":[{"name":"accepted values","values":["ambulatory","wellness","emergency","urgentcare","outpatient","inpatient"]},{"name":"not null"}]},{"name":"encounter_code","description":"SNOMED CT code for the encounter type"},{"name":"encounter_description","description":"Description of the encounter type"},{"name":"encounter_end_at","description":"End timestamp of the encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_id","description":"Unique encounter identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"encounter_start_at","description":"Start timestamp of the encounter","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"organization_id","description":"Foreign key to the organization","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__organizations.organization_id"}]},{"name":"patient_id","description":"Foreign key to the patient","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__patients.patient_id"}]},{"name":"payer_coverage","description":"Amount covered by payer","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"payer_id","description":"Foreign key to the payer","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__payers.payer_id"}]},{"name":"provider_id","description":"Foreign key to the provider","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__providers.provider_id"}]},{"name":"reason_code","description":"SNOMED CT code for the reason of visit"},{"name":"reason_description","description":"Description of the reason for visit"},{"name":"total_claim_cost","description":"Total claim cost","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"stg_synthea__medications":{"description":"Staging model for prescribed medications. One row per medication prescription with surrogate key.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"base_cost","description":"Base cost per dispense","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"dispenses","description":"Number of times medication was dispensed","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_id","description":"Foreign key to the encounter","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__encounters.encounter_id"}]},{"name":"medication_code","description":"RxNorm code for the medication","tests":[{"name":"not null"}]},{"name":"medication_description","description":"Description of the medication","tests":[{"name":"not null"}]},{"name":"medication_end_at","description":"Timestamp when medication ended (null if ongoing)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"medication_id","description":"Surrogate key for the medication record","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"medication_start_at","description":"Timestamp when medication was prescribed","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"patient_id","description":"Foreign key to the patient","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__patients.patient_id"}]},{"name":"payer_coverage","description":"Amount covered by payer","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"payer_id","description":"Foreign key to the payer","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__payers.payer_id"}]},{"name":"reason_code","description":"SNOMED CT code for the reason of medication"},{"name":"reason_description","description":"Description of the reason for medication"},{"name":"total_cost","description":"Total cost of all dispenses","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"stg_synthea__observations":{"description":"Staging model for clinical observations (vital signs, lab results). One row per observation with surrogate key.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"encounter_id","description":"Foreign key to the encounter. Note: ~10% of observations have null encounter_id (from external sources or historical data imports).\n","tests":[{"name":"relationships","detail":"stg_synthea__encounters.encounter_id"}]},{"name":"observation_at","description":"Timestamp when observation was recorded","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"observation_code","description":"LOINC code for the observation","tests":[{"name":"not null"}]},{"name":"observation_description","description":"Description of the observation","tests":[{"name":"not null"}]},{"name":"observation_id","description":"Surrogate key for the observation record","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"observation_type","description":"Type of observation (numeric, text, etc.)"},{"name":"observation_value","description":"Value of the observation (stored as string)"},{"name":"patient_id","description":"Foreign key to the patient","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__patients.patient_id"}]},{"name":"units","description":"Units of measurement"}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"stg_synthea__organizations":{"description":"Staging model for healthcare organizations/facilities. One row per organization with location and performance metrics.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"address","description":"Street address"},{"name":"city","description":"City"},{"name":"latitude","description":"Latitude coordinate"},{"name":"longitude","description":"Longitude coordinate"},{"name":"organization_id","description":"Unique organization identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"organization_name","description":"Name of the healthcare organization","tests":[{"name":"not null"}]},{"name":"phone","description":"Phone number"},{"name":"revenue","description":"Total revenue","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"state","description":"State (full state name)"},{"name":"utilization","description":"Total utilization count","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"zip_code","description":"ZIP code","tests":[{"name":"dbt_expectations.expect_column_values_to_match_regex"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"stg_synthea__patients":{"description":"Staging model for patient demographics and identifiers. One row per patient with personal information, location, and financial data.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"address","description":"Street address"},{"name":"birth_date","description":"Patient date of birth","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"birth_place","description":"Place of birth"},{"name":"city","description":"City of residence"},{"name":"county","description":"County of residence"},{"name":"death_date","description":"Patient date of death (null if alive)","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"drivers_license","description":"Driver's license number"},{"name":"ethnicity","description":"Patient ethnicity (hispanic or nonhispanic)"},{"name":"first_name","description":"Patient's first name","tests":[{"name":"not null"}]},{"name":"gender","description":"Patient gender (M or F)","tests":[{"name":"accepted values","values":["M","F"]},{"name":"dbt_expectations.expect_column_values_to_match_regex"},{"name":"not null"}]},{"name":"healthcare_coverage","description":"Total healthcare coverage received","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"healthcare_expenses","description":"Total healthcare expenses incurred","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"last_name","description":"Patient's last name","tests":[{"name":"not null"}]},{"name":"latitude","description":"Latitude coordinate of residence"},{"name":"longitude","description":"Longitude coordinate of residence"},{"name":"maiden_name","description":"Maiden name (if applicable)"},{"name":"marital_status","description":"Marital status (M=Married, S=Single, or blank)"},{"name":"name_prefix","description":"Name prefix (Mr., Mrs., Ms., etc.)"},{"name":"name_suffix","description":"Name suffix (Jr., Sr., III, etc.)"},{"name":"passport_number","description":"Passport number"},{"name":"patient_id","description":"Unique patient identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"race","description":"Patient race"},{"name":"ssn_hash","description":"MD5 hash of Social Security Number (masked for privacy)"},{"name":"state","description":"State of residence (full state name, e.g., Massachusetts)"},{"name":"zip_code","description":"ZIP code","tests":[{"name":"dbt_expectations.expect_column_values_to_match_regex"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"stg_synthea__payers":{"description":"Staging model for insurance payers. One row per payer with contact information and aggregate metrics.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"address","description":"Street address"},{"name":"amount_covered","description":"Total amount covered by payer","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"amount_uncovered","description":"Total amount not covered by payer"},{"name":"average_quality_of_life_score","description":"Average quality of life score for members"},{"name":"city","description":"City"},{"name":"covered_encounters","description":"Number of encounters covered"},{"name":"covered_immunizations","description":"Number of immunizations covered"},{"name":"covered_medications","description":"Number of medications covered"},{"name":"covered_procedures","description":"Number of procedures covered"},{"name":"member_months","description":"Total member months"},{"name":"payer_id","description":"Unique payer identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"payer_name","description":"Name of the insurance payer","tests":[{"name":"not null"}]},{"name":"phone","description":"Phone number"},{"name":"revenue","description":"Total revenue collected","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"state","description":"State where headquartered"},{"name":"uncovered_encounters","description":"Number of encounters not covered"},{"name":"uncovered_immunizations","description":"Number of immunizations not covered"},{"name":"uncovered_medications","description":"Number of medications not covered"},{"name":"uncovered_procedures","description":"Number of procedures not covered"},{"name":"unique_customers","description":"Number of unique customers"},{"name":"zip_code","description":"ZIP code (stored as numeric, 5 digits)"}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"stg_synthea__procedures":{"description":"Staging model for medical procedures performed. One row per procedure instance with surrogate key.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"base_cost","description":"Base cost of the procedure","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"encounter_id","description":"Foreign key to the encounter","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__encounters.encounter_id"}]},{"name":"patient_id","description":"Foreign key to the patient","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__patients.patient_id"}]},{"name":"procedure_at","description":"Timestamp when the procedure was performed","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"},{"name":"not null"}]},{"name":"procedure_code","description":"SNOMED CT code for the procedure","tests":[{"name":"not null"}]},{"name":"procedure_description","description":"Description of the procedure","tests":[{"name":"not null"}]},{"name":"procedure_id","description":"Surrogate key for the procedure record","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"reason_code","description":"SNOMED CT code for the reason of the procedure"},{"name":"reason_description","description":"Description of the reason for the procedure"}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"stg_synthea__providers":{"description":"Staging model for healthcare providers (doctors, nurses, etc.). One row per provider with specialization and affiliated organization.\n","materialized":"view","columns":[{"name":"_loaded_at","description":"Timestamp when record was loaded into staging"},{"name":"address","description":"Street address"},{"name":"city","description":"City"},{"name":"gender","description":"Provider gender (M or F)","tests":[{"name":"accepted values","values":["M","F"]},{"name":"dbt_expectations.expect_column_values_to_match_regex"},{"name":"not null"}]},{"name":"latitude","description":"Latitude coordinate"},{"name":"longitude","description":"Longitude coordinate"},{"name":"organization_id","description":"Foreign key to the provider's organization","tests":[{"name":"not null"},{"name":"relationships","detail":"stg_synthea__organizations.organization_id"}]},{"name":"provider_id","description":"Unique provider identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"provider_name","description":"Full name of the provider","tests":[{"name":"not null"}]},{"name":"specialty","description":"Medical specialty"},{"name":"state","description":"State (full state name)"},{"name":"utilization","description":"Total utilization count","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"zip_code","description":"ZIP code","tests":[{"name":"dbt_expectations.expect_column_values_to_match_regex"}]}],"model_tests":[{"name":"dbt_expectations.expect_table_row_count_to_be_between"}]},"v_encounter_summary":{"description":"Enriched encounter view with dimension attributes for ad-hoc analysis.\nEphemeral (not persisted) - used as a building block for other queries.\nJoins encounters with patient, provider, organization, and payer details.\n\nUse cases:\n- Ad-hoc encounter analysis\n- Building block for custom reports\n- Quick encounter lookups with full context\n","materialized":"ephemeral","tags":["analytics","marts","view"],"columns":[{"name":"encounter_class","description":"Type of encounter"},{"name":"encounter_date","description":"Date of the encounter"},{"name":"encounter_id","description":"Unique encounter identifier"},{"name":"organization_id","description":"Organization identifier"},{"name":"organization_name","description":"Organization name"},{"name":"patient_id","description":"Patient identifier"},{"name":"patient_name","description":"Full patient name"},{"name":"patient_responsibility","description":"Amount owed by patient"},{"name":"payer_coverage","description":"Amount covered by insurance"},{"name":"payer_id","description":"Payer identifier"},{"name":"payer_name","description":"Payer name"},{"name":"provider_id","description":"Provider identifier"},{"name":"provider_name","description":"Full provider name"},{"name":"total_cost","description":"Total claim cost"}]},"v_patient_current_conditions":{"description":"Current (active) conditions for each patient, filtered from fct_condition_cohorts.\nUse for patient panels, disease management dashboards, and care gap identification.\nGrain: (patient_id, condition_code) - only active conditions\n\nUse cases:\n- Patient panel management\n- Active disease registries\n- Care gap identification\n- Real-time patient condition views\n","materialized":"table","tags":["analytics","marts","view"],"columns":[{"name":"condition_code","description":"ICD/SNOMED condition code"},{"name":"condition_description","description":"Full condition name"},{"name":"condition_key","description":"Foreign key to dim_conditions","tests":[{"name":"relationships","detail":"dim_conditions.condition_key"}]},{"name":"encounter_count","description":"Number of encounters with this condition"},{"name":"first_diagnosis_date","description":"Date of first diagnosis"},{"name":"months_with_condition","description":"Duration of condition in months"},{"name":"patient_id","description":"Natural patient identifier"},{"name":"patient_key","description":"Foreign key to dim_patients"}]},"v_provider_active_patients":{"description":"Active patient count per provider for panel management and workload analysis.\nAggregates patients with active conditions by their treating provider.\nGrain: provider_id\n\nUse cases:\n- Provider panel size management\n- Workload distribution analysis\n- Capacity planning\n- Provider assignment optimization\n","materialized":"table","tags":["analytics","marts","view"],"columns":[{"name":"active_patient_count","description":"Number of patients with active conditions","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"avg_conditions_per_patient","description":"Average number of active conditions per patient","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]},{"name":"organization_id","description":"Natural organization identifier"},{"name":"organization_key","description":"Foreign key to dim_organizations"},{"name":"provider_id","description":"Natural provider identifier","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"provider_key","description":"Foreign key to dim_providers","tests":[{"name":"not null"},{"name":"unique"}]},{"name":"provider_name","description":"Full name of the provider"},{"name":"total_active_conditions","description":"Total number of active conditions managed","tests":[{"name":"dbt_expectations.expect_column_values_to_be_between"}]}]}},"check_specs":{"grain.unique-key-unbacked":{"name":"Unique key without a uniqueness test","group":"grain","tier":"total","instrument":"data-test","conditions":["the model declares config.unique_key (a column name or a list of columns)","no enabled uniqueness data test (unique, or a composite unique_combination_of_columns) attached to the model has a column set that is a subset of the declared key"],"exclusions":["a unique_key value that is not a literal column name / list of column names is reported UNKNOWN, never UNCOVERED (the declared grain is not statically recoverable)","a uniqueness test whose column set is WIDER than the key does not satisfy the check (uniqueness of a superset does not imply uniqueness at the declared grain)"],"rationale":"Incremental merge / delete+insert semantics silently depend on the declared unique_key actually being unique — a duplicate key corrupts the merge with no test to catch it. Declaring a grain without a test at that grain is an unverified load-bearing assumption.","book_href":"https://breezy-bays-labs.github.io/cute-dbt/checks/grain.unique-key-unbacked.html"},"incremental.branch-coverage":{"name":"Unexercised is_incremental() branch","group":"incremental","tier":"high","instrument":"unit-test","conditions":["the model is materialized incremental (config.materialized = \"incremental\") — its body forks on is_incremental(), and a dbt unit test compiles exactly one side of that fork","a unit test with overrides.macros.is_incremental = true exercises the incremental branch; an explicit false override OR no override at all exercises the initial full-build branch (dbt compiles is_incremental() as false in unit tests by default)","branch coverage rolls up per model as none / false-only / true-only / both; only BOTH satisfies the construct, attributing every unit test on the model (each test compiles one side of the fork)","the HIGH-tier cue boundary (the union.arm-coverage precedent): a test on a branch proves that branch's compiled SQL runs under fixtures — whether the branch's filter/merge semantics are meaningfully asserted, or whether the body's Jinja even calls is_incremental(), is not statically decidable from the manifest, so the recommendation is a cue, never an assertion of a bug"],"exclusions":["models whose materialization is absent, non-string, or anything other than incremental (view, table, ephemeral, custom) emit no finding — when the fork provably cannot exist or cannot be statically known, the check is silent, never misclassifies","microbatch-strategy models (incremental_strategy = \"microbatch\", or any non-null event_time config) are OUT of rule #1: dbt replays them through event-time batch windows, not the is_incremental() fork, so true/false override coverage does not describe their semantics — never classified","a non-boolean is_incremental override collapses to the no-override default at ingestion (cute-dbt#145 tolerant truthiness) and counts toward the full-build branch — the conservative side of the cue"],"rationale":"An incremental model is two programs in one body: the initial full build, and the incremental run that filters on the high-water mark and merges by key. Each unit test compiles only one of them, so a suite living entirely on one branch ships the other untested — exactly where incremental models silently drop, duplicate, or re-process rows.","book_href":"https://breezy-bays-labs.github.io/cute-dbt/checks/incremental.branch-coverage.html"},"join.left-null-propagation":{"name":"LEFT JOIN null propagation untested","group":"join","tier":"high","instrument":"both","conditions":["the model LEFT-JOINs a relation and right-side columns provably reach the containing SELECT's projection: a direct `\u003cright>.\u003ccolumn>` item, a `\u003cright>.*` qualified wildcard, or a bare `*`","satisfaction: some unit test's literal givens carry a left-side row whose ON equi-key has no match among the right-side given rows — cells compare on the value-normalized equality key, and a left row whose key cell is NULL or absent never matches (SQL join semantics), so it exercises the no-match path","given binding follows the union.arm-coverage premise: only `given` entries carry statically-visible rows — an ungiven non-seed input is an empty mock; join sides bind to givens directly by external leaf name or through an upstream closure of simple-FROM CTEs reading exactly one external relation","instrument routing (catalog C4/C10): when the SELECT containing the LEFT JOIN dedups its output with DISTINCT — the dedup-after-fan-out signal — the data-test recommendation wins: prove the right key's grain with a uniqueness data test at the source instead of adding fixtures","verdict order: any test exercising an unmatched left row makes the construct COVERED with attribution; otherwise any statically-unattributable binding or given makes it UNKNOWN; otherwise UNCOVERED"],"exclusions":["right-side columns reaching the output only through expressions (COALESCE, CASE, function calls) are not attributed — the construct stays silent unless a direct right-qualified item or wildcard projects (conservative: never a false fire)","non-equi or non-column ON predicates, USING / NATURAL constraints, and unqualified key columns leave the join key statically unrecoverable — verdict UNKNOWN, never UNCOVERED","a derived-table join side emits no fact; a CTE side whose upstream closure is not a single-external chain of simple-FROM CTEs is UNKNOWN, never UNCOVERED","external `fixture:` files and non-literal `format: sql` givens make a test statically uncountable — UNKNOWN, never UNCOVERED","an ungiven seed-side input reads real seed data — UNKNOWN, never UNCOVERED"],"rationale":"A LEFT JOIN whose right-side columns reach the output propagates NULLs on every unmatched left row — the most common real dbt unit-test catch. When every left given row has a right match, the no-match path runs on zero rows in every test, so an unhandled NULL (or a wrong fallback) ships silently.","book_href":"https://breezy-bays-labs.github.io/cute-dbt/checks/join.left-null-propagation.html"},"union.arm-coverage":{"name":"Unexercised UNION arm","group":"union","tier":"high","instrument":"unit-test","conditions":["the model's body (or a CTE within it) UNIONs arms the CTE engine resolved to union-typed edges — each checked arm is a join-free reference to an earlier CTE (`UnionAll` / `UnionDistinct`)","an arm counts as exercised when at least one unit-test given with one or more in-manifest rows binds — by `ref(...)` / `source(...)` leaf name, case-insensitive — to any external relation in the arm's upstream CTE closure","a given bound to a relation shared by several arms exercises every arm whose closure reads it: its rows provably enter each arm's scan, while per-arm filter survival is deliberately out of scope (no predicate evaluation) — the HIGH-tier cue boundary, never an assertion of output-level coverage","verdict order: any provably-unfed arm makes the construct UNCOVERED; otherwise any statically-unattributable arm makes it UNKNOWN; otherwise COVERED, attributing every test that feeds an arm"],"exclusions":["arms that are not a join-free reference to an earlier CTE (join chains, derived tables, arms reading external tables directly, EXCEPT/INTERSECT arms) emit no union edge and are invisible to this check — never counted, never reported","an arm whose upstream closure reads no resolvable external relation (constant SELECT, table functions) makes the construct UNKNOWN, never UNCOVERED","an arm fed only by external-fixture or non-literal-sql givens (row counts not statically recoverable) makes the construct UNKNOWN, never UNCOVERED","an arm whose only unbound feeding relation resolves to a seed is UNKNOWN, never UNCOVERED, when the model has unit tests (dbt lets seed inputs go ungiven and reads the real seed file)","`this` givens (incremental prior state) never feed a union arm"],"rationale":"A UNION arm with no fixture rows contributes nothing to any unit test: its projection, casts, and filters run on zero rows, so a column mix-up or a dropped row in that arm ships silently. One given row per arm makes every branch's contribution visible in the expected output.","book_href":"https://breezy-bays-labs.github.io/cute-dbt/checks/union.arm-coverage.html"}}}</script>
+<script>
+
+/* cute-dbt explore tests viewer v1 (cute-dbt#102)
+   ----------------------------------------------------------------------------
+   The unit-test viewer on explore's tests.html: renders the selected
+   test's description, badges, given fixtures and expected table into the
+   SHARED test-card partial (templates/partials/test-card.html — the same
+   markup report.html renders), reading the embedded `cute-dbt-data`
+   ReportPayload (the build_payload reuse seam).
+
+   Deliberately a LIGHT sibling of the report's interaction engine, not a
+   copy: no jQuery, no DataTables, no diff toggles (explore is
+   full-manifest — there is no changed-set and no PR diff to tint), no
+   Mermaid/Cytoscape. The Current-view fixture grids render the SAME
+   Rust-computed FixtureTable POD ({display, key} cells, cute-dbt#138)
+   the report renders, so the two surfaces cannot drift on cell
+   semantics.
+
+   Affordances:
+   - the test selector (the partial's #test-select) lists every unit
+     test, optgrouped by model;
+   - each index row's test-name button (data-test-id) selects that test
+     in the viewer;
+   - NULL / absent cells keep the report's vocabulary (.cell-null /
+     .cell-absent); sql-format fixtures render as a code block; external
+     fixture files surface the provenance note instead of a silently
+     empty grid (the cute-dbt#126 contract).
+
+   DOM discipline: every dynamic string lands via createElement +
+   textContent — never an HTML-string sink (the asset_embed banner test
+   pins this). First-party, NOT vendored: lives at templates/explore-tests.js,
+   embedded via asset_embed::EXPLORE_TESTS_JS (include_str!). Banner-pin
+   + end-of-file-sentinel tests guard the include. */
+(function () {
+  "use strict";
+
+  var carrier = document.getElementById("cute-dbt-data");
+  var viewer = document.querySelector(".explore-viewer");
+  var select = document.getElementById("test-select");
+  if (!carrier || !viewer || !select) return;
+  var data = JSON.parse(carrier.textContent);
+
+  // Flat id -> {model, test} index over the payload (prototype-less so a
+  // hostile test id can never collide with a built-in property).
+  var byId = Object.create(null);
+  var total = 0;
+  (data.models || []).forEach(function (m) {
+    (m.tests || []).forEach(function (t) {
+      byId[t.id] = { model: m, test: t };
+      total += 1;
+    });
+  });
+  if (!total) {
+    viewer.hidden = true;
+    return;
+  }
+
+  // ---- tiny DOM helpers (textContent only) --------------------------------
+  function el(tag, cls, text) {
+    var node = document.createElement(tag);
+    if (cls) node.className = cls;
+    if (text !== undefined) node.textContent = text;
+    return node;
+  }
+
+  function clear(node) {
+    while (node.firstChild) node.removeChild(node.firstChild);
+  }
+
+  function rowsText(n) {
+    return n + " row" + (n === 1 ? "" : "s");
+  }
+
+  // ---- fixture-shape predicates (the interaction.js vocabulary) -----------
+  function isSqlCodeBlock(obj) {
+    return Boolean(obj && obj.format === "sql" && typeof obj.rows === "string");
+  }
+
+  function isExternalFixture(obj) {
+    return Boolean(obj && obj.fixture && (obj.rows === null || obj.rows === undefined));
+  }
+
+  function isLoadedExternalFixture(obj) {
+    return Boolean(obj && obj.fixture && obj.rows !== null && obj.rows !== undefined);
+  }
+
+  function provenanceChip(name) {
+    var chip = el("span", "fixture-provenance", "from ");
+    chip.appendChild(el("code", "", String(name)));
+    return chip;
+  }
+
+  function externalNote(name) {
+    var box = el("div", "given-empty external-fixture-note",
+      "data in external fixture file: ");
+    box.appendChild(el("code", "", String(name)));
+    return box;
+  }
+
+  function sqlBlock(text) {
+    var pre = el("pre", "sql-block");
+    pre.appendChild(el("code", "", String(text)));
+    return pre;
+  }
+
+  // ---- the Current-view grid off the Rust FixtureTable POD ----------------
+  function cellTd(cell) {
+    var td = document.createElement("td");
+    var key = cell && cell.key;
+    if (!key || key.t === "null") {
+      td.className = "cell-null";
+      td.textContent = "NULL";
+      return td;
+    }
+    if (key.t === "absent") {
+      td.className = "cell-absent";
+      return td;
+    }
+    if (key.t === "number") td.className = "cell-num";
+    td.textContent = cell.display;
+    return td;
+  }
+
+  function buildTable(table, cls) {
+    var tbl = el("table", cls);
+    var thead = document.createElement("thead");
+    var hr = document.createElement("tr");
+    (table.columns || []).forEach(function (c) {
+      hr.appendChild(el("th", "", c));
+    });
+    thead.appendChild(hr);
+    tbl.appendChild(thead);
+    var tbody = document.createElement("tbody");
+    (table.rows || []).forEach(function (r) {
+      var tr = document.createElement("tr");
+      (r.cells || []).forEach(function (cell) {
+        tr.appendChild(cellTd(cell));
+      });
+      tbody.appendChild(tr);
+    });
+    tbl.appendChild(tbody);
+    return tbl;
+  }
+
+  // ---- per-test render -----------------------------------------------------
+  function renderGiven(g) {
+    var sec = el("section", "given-section");
+    var hdr = el("div", "table-header");
+    hdr.appendChild(el("h4", "table-title", "given · " + g.input));
+    if (g.is_this) hdr.appendChild(el("span", "this-badge", "prior model state"));
+    if (isLoadedExternalFixture(g)) hdr.appendChild(provenanceChip(g.fixture));
+    if (isSqlCodeBlock(g)) {
+      hdr.appendChild(el("span", "format-badge", "format: sql"));
+      sec.appendChild(hdr);
+      sec.appendChild(sqlBlock(g.rows));
+      return sec;
+    }
+    if (isExternalFixture(g)) {
+      if (g.format) hdr.appendChild(el("span", "format-badge", "format: " + g.format));
+      sec.appendChild(hdr);
+      sec.appendChild(externalNote(g.fixture));
+      return sec;
+    }
+    var table = g.table || { columns: [], rows: [] };
+    if (g.format && g.format !== "dict") {
+      hdr.appendChild(el("span", "format-badge", "format: " + g.format));
+    }
+    hdr.appendChild(el("span", "row-count-badge", rowsText(table.rows.length)));
+    sec.appendChild(hdr);
+    sec.appendChild(buildTable(table, "given-table"));
+    return sec;
+  }
+
+  function renderExpected(t) {
+    var body = document.querySelector(".expected-body");
+    var rowcount = document.querySelector(".expected-rowcount");
+    clear(body);
+    if (isLoadedExternalFixture(t.expected)) {
+      body.appendChild(provenanceChip(t.expected.fixture));
+    }
+    if (isSqlCodeBlock(t.expected)) {
+      rowcount.textContent = "format: sql";
+      body.appendChild(sqlBlock(t.expected.rows));
+      return;
+    }
+    if (isExternalFixture(t.expected)) {
+      rowcount.textContent = "external fixture";
+      body.appendChild(externalNote(t.expected.fixture));
+      return;
+    }
+    var table = (t.expected && t.expected.table) || { columns: [], rows: [] };
+    rowcount.textContent = rowsText(table.rows.length);
+    body.appendChild(buildTable(table, "expected-table"));
+  }
+
+  function renderTest(t) {
+    // Description (the partial's hidden-when-absent contract).
+    var desc = document.querySelector(".test-description");
+    if (t.description) {
+      desc.textContent = t.description;
+      desc.hidden = false;
+    } else {
+      desc.textContent = "";
+      desc.hidden = true;
+    }
+    // Badges: tag chips (kept light — explore has no diff badges).
+    var badges = document.querySelector(".test-badges");
+    clear(badges);
+    (t.tags || []).forEach(function (tag) {
+      badges.appendChild(el("span", "tag-badge", tag));
+    });
+    // Details body: where the test was authored.
+    var details = document.querySelector(".test-details-body");
+    clear(details);
+    if (t.defined_in) {
+      var p = el("p", "test-defined-in", "defined in ");
+      p.appendChild(el("code", "", t.defined_in));
+      details.appendChild(p);
+    }
+    // Given panel.
+    var givenWrap = document.querySelector(".left-panel-body");
+    clear(givenWrap);
+    if (!t.given || !t.given.length) {
+      givenWrap.appendChild(el("div", "empty-hint", "No fixtures defined for this test."));
+    } else {
+      t.given.forEach(function (g) { givenWrap.appendChild(renderGiven(g)); });
+    }
+    // Expected panel.
+    renderExpected(t);
+  }
+
+  function selectTest(id) {
+    var entry = byId[id];
+    if (!entry) return;
+    if (select.value !== id) select.value = id;
+    renderTest(entry.test);
+  }
+
+  // ---- selector population + wiring ----------------------------------------
+  (data.models || []).forEach(function (m) {
+    if (!m.tests || !m.tests.length) return;
+    var og = document.createElement("optgroup");
+    og.label = m.name;
+    m.tests.forEach(function (t) {
+      var opt = document.createElement("option");
+      opt.value = t.id;
+      opt.textContent = t.name;
+      og.appendChild(opt);
+    });
+    select.appendChild(og);
+  });
+
+  select.addEventListener("change", function () { selectTest(select.value); });
+
+  // Index rows: each test-name button jumps the viewer to its test.
+  Array.prototype.forEach.call(
+    document.querySelectorAll(".test-jump[data-test-id]"),
+    function (btn) {
+      btn.addEventListener("click", function () {
+        selectTest(btn.getAttribute("data-test-id"));
+        if (viewer.scrollIntoView) viewer.scrollIntoView({ block: "start" });
+      });
+    }
+  );
+
+  // Boot: the first test in payload order.
+  selectTest(select.value);
+})();
+/* end of cute-dbt explore tests viewer v1 (cute-dbt#102) */
+
+</script>
 </body>
 </html>
\ No newline at end of file
diff --git a/src/adapters/asset_embed.rs b/src/adapters/asset_embed.rs
index 63d8ba0e..d31e3e24 100644
--- a/src/adapters/asset_embed.rs
+++ b/src/adapters/asset_embed.rs
@@ -132,6 +132,40 @@ pub const THEME_JS: &str = include_str!("../../templates/theme.js");
 /// [`LineagePayload`]: crate::adapters::explore::LineagePayload
 pub const EXPLORE_LINEAGE_JS: &str = include_str!("../../templates/explore-lineage.js");
 
+/// The explore page's first-party CTE-view engine (cute-dbt#102) — the
+/// CTE ⇄ model view toggle on `dag.html` plus the per-model Cytoscape
+/// CTE DAG it renders for the highlighted model: dagre left-to-right
+/// layout (the vendored extension is already on the page), role-styled
+/// nodes (final / import / transform — the report's vocabulary),
+/// join-type-labeled edges, and the fail-open degraded view for a
+/// `not_compiled` model (labeled, never an error). Same init hygiene as
+/// [`EXPLORE_LINEAGE_JS`]: canvas-text labels, system `fontFamily`,
+/// measured node widths (no `width: label`), no workers, handlers bound
+/// from our JS, in-place class mutation per interaction (a view switch
+/// or model retarget is a view change and may rebuild the CTE
+/// instance; the lineage instance is never rebuilt).
+///
+/// First-party, NOT vendored: lives at `templates/explore-cte.js`.
+/// Integrity gates: the banner-pin + end-of-file sentinel test in this
+/// module.
+pub const EXPLORE_CTE_JS: &str = include_str!("../../templates/explore-cte.js");
+
+/// The explore page's first-party unit-test viewer engine (cute-dbt#102)
+/// — renders the selected test's description, given fixtures and
+/// expected table into the shared test-card partial on `tests.html`,
+/// reading the embedded `cute-dbt-data` [`ReportPayload`] (the
+/// `build_payload` reuse seam). DOM built with `createElement` +
+/// `textContent` only; no jQuery, no `DataTables`, no graph engine —
+/// the page stays a light static-plus-viewer surface and passes the
+/// zero-egress gate on its own.
+///
+/// First-party, NOT vendored: lives at `templates/explore-tests.js`.
+/// Integrity gates: the banner-pin + end-of-file sentinel test in this
+/// module.
+///
+/// [`ReportPayload`]: crate::adapters::render::ReportPayload
+pub const EXPLORE_TESTS_JS: &str = include_str!("../../templates/explore-tests.js");
+
 /// The report's first-party Cytoscape DAG engine (cute-dbt#180) — the
 /// opt-in interactive alternative behind the settings-panel engine
 /// picker: longest-path preset layout (no layout plugin), canvas-text
@@ -238,6 +272,48 @@ mod tests {
         );
     }
 
+    #[test]
+    fn the_explore_cte_js_carries_its_banner_and_is_not_truncated() {
+        assert!(
+            EXPLORE_CTE_JS.contains("cute-dbt explore CTE engine v1"),
+            "explore-cte.js head banner",
+        );
+        assert!(
+            EXPLORE_CTE_JS
+                .trim_end()
+                .ends_with("/* end of cute-dbt explore CTE engine v1 (cute-dbt#102) */"),
+            "explore-cte.js end-of-file sentinel (truncation guard)",
+        );
+        // The focus-commit contract (epic #99): the CTE view must never
+        // grow a second selectedModel write site — the Space commit in
+        // explore-lineage.js stays the only one.
+        assert!(
+            !EXPLORE_CTE_JS.contains("dataset.selectedModel ="),
+            "explore-cte.js must not write the focus-commit signal",
+        );
+    }
+
+    #[test]
+    fn the_explore_tests_js_carries_its_banner_and_is_not_truncated() {
+        assert!(
+            EXPLORE_TESTS_JS.contains("cute-dbt explore tests viewer v1"),
+            "explore-tests.js head banner",
+        );
+        assert!(
+            EXPLORE_TESTS_JS
+                .trim_end()
+                .ends_with("/* end of cute-dbt explore tests viewer v1 (cute-dbt#102) */"),
+            "explore-tests.js end-of-file sentinel (truncation guard)",
+        );
+        // The viewer builds DOM with createElement + textContent only —
+        // innerHTML over payload-derived strings would reopen the XSS
+        // surface the canvas-label discipline closed.
+        assert!(
+            !EXPLORE_TESTS_JS.contains("innerHTML"),
+            "explore-tests.js must never assign innerHTML",
+        );
+    }
+
     #[test]
     fn the_favicon_is_an_empty_data_uri() {
         assert_eq!(FAVICON_DATA_URI, "data:,");
diff --git a/src/adapters/explore.rs b/src/adapters/explore.rs
index ce7cee35..14bfa210 100644
--- a/src/adapters/explore.rs
+++ b/src/adapters/explore.rs
@@ -37,7 +37,7 @@
 //! are same-directory navigation anchors (`dag.html` ⇄ `tests.html`),
 //! which load nothing until clicked and resolve over `file://`.
 
-use std::collections::HashMap;
+use std::collections::{BTreeMap, HashMap};
 use std::fs;
 use std::io;
 use std::path::Path;
@@ -46,9 +46,10 @@ use askama::Template;
 use serde::Serialize;
 
 use crate::adapters::asset_embed::{
-    CYTOSCAPE_DAGRE_JS, CYTOSCAPE_JS, EXPLORE_LINEAGE_JS, FAVICON_DATA_URI, SAKURA_CSS,
+    CYTOSCAPE_DAGRE_JS, CYTOSCAPE_JS, EXPLORE_CTE_JS, EXPLORE_LINEAGE_JS, EXPLORE_TESTS_JS,
+    FAVICON_DATA_URI, SAKURA_CSS,
 };
-use crate::adapters::render::ReportPayload;
+use crate::adapters::render::{DagPayload, ReportPayload};
 use crate::domain::{Manifest, ModelInScopeSet, NodeId};
 
 /// One model node in the lineage graph.
@@ -157,6 +158,15 @@ pub struct LineagePayload {
     pub nodes: Vec<LineageNodePayload>,
     /// Forward dependency edges between models in `nodes`, ordered.
     pub edges: Vec<LineageEdgePayload>,
+    /// Per-model CTE DAGs (cute-dbt#102) — the CTE ⇄ model view
+    /// toggle's data, keyed by full model node id. Each entry is the
+    /// SAME [`DagPayload`] the report renders for that model (the
+    /// `build_payload` reuse seam): engine-extracted CTE nodes with
+    /// render-classified roles plus join-typed edges. Models with an
+    /// empty graph carry **no** entry — the client renders the
+    /// "no CTE DAG" sparse state for a compiled CTE-less model and the
+    /// labeled fail-open degraded view for a `not_compiled` one.
+    pub cte_dags: BTreeMap<String, DagPayload>,
 }
 
 /// Build the serializable lineage payload for `dag.html` (cute-dbt#101).
@@ -185,7 +195,37 @@ pub fn build_lineage_payload(current: &Manifest, models: &ModelInScopeSet) -> Li
             not_compiled: n.not_compiled,
         })
         .collect();
-    LineagePayload { nodes, edges }
+    LineagePayload {
+        nodes,
+        edges,
+        cte_dags: BTreeMap::new(),
+    }
+}
+
+/// Build the per-model CTE-DAG map for the dag.html carrier
+/// (cute-dbt#102) — the CTE ⇄ model view toggle's data.
+///
+/// Pure zip over the documented one-to-one contract between `models`
+/// and `payload.models` (see the private `explore_models` assembler
+/// below, which documents the zip's soundness): each model id keys
+/// its payload entry's [`DagPayload`] — the same engine-extracted,
+/// role-classified graph the report renders, parsed exactly once during
+/// `build_payload`. Models whose graph is empty (an uncompiled
+/// `dbt parse` node, or compiled SQL with no `WITH` clause) contribute
+/// **no** entry, keeping the carrier lean; the client distinguishes the
+/// two off the lineage node's `not_compiled` flag (fail-open: the
+/// degraded view is labeled, never an error).
+#[must_use]
+pub fn cte_dags_by_model(
+    models: &ModelInScopeSet,
+    payload: &ReportPayload,
+) -> BTreeMap<String, DagPayload> {
+    models
+        .iter()
+        .zip(payload.models.iter())
+        .filter(|(_, model_payload)| !model_payload.dag.nodes.is_empty())
+        .map(|(id, model_payload)| (id.as_str().to_owned(), model_payload.dag.clone()))
+        .collect()
 }
 
 /// One model section on `tests.html` (server-rendered).
@@ -205,6 +245,9 @@ struct ExploreModel {
 
 /// One unit-test row on `tests.html`.
 struct ExploreTest {
+    /// Manifest unit-test id — the `data-test-id` handle the index row
+    /// carries so the viewer (cute-dbt#102) can select it in place.
+    id: String,
     /// User-facing test name.
     name: String,
     /// Optional `description:` from the manifest.
@@ -241,6 +284,9 @@ struct ExploreDagTemplate<'a> {
     cytoscape_js: &'a str,
     cytoscape_dagre_js: &'a str,
     explore_lineage_js: &'a str,
+    /// First-party CTE-view engine (cute-dbt#102) — the CTE ⇄ model
+    /// view toggle and the per-model Cytoscape CTE DAG.
+    explore_cte_js: &'a str,
     favicon_data_uri: &'a str,
     /// Pre-escaped JSON for the `explore-dag-data` carrier (the
     /// [`LineagePayload`]).
@@ -259,6 +305,10 @@ struct ExploreTestsTemplate<'a> {
     models: &'a [ExploreModel],
     model_count: usize,
     test_count: usize,
+    /// First-party unit-test viewer engine (cute-dbt#102) — renders the
+    /// selected test's fixtures into the shared test-card partial from
+    /// the embedded payload.
+    explore_tests_js: &'a str,
     /// Pre-escaped JSON for the `cute-dbt-data` carrier (the full
     /// [`ReportPayload`] — the `build_payload` reuse seam).
     payload_json: &'a str,
@@ -322,6 +372,7 @@ fn explore_models(
                     .tests
                     .iter()
                     .map(|t| ExploreTest {
+                        id: t.id.clone(),
                         name: t.name.clone(),
                         description: t.description.clone(),
                         shape: test_shape(
@@ -355,7 +406,10 @@ pub fn render_explore(
 ) -> io::Result<()> {
     fs::create_dir_all(out_dir)?;
 
-    let lineage = build_lineage_payload(current, models);
+    let mut lineage = build_lineage_payload(current, models);
+    // cute-dbt#102 — the CTE ⇄ model toggle's per-model CTE DAGs ride
+    // the same carrier (the payload's graphs, parsed once upstream).
+    lineage.cte_dags = cte_dags_by_model(models, payload);
     let not_compiled_count = lineage.nodes.iter().filter(|n| n.not_compiled).count();
     let dag_json = json_for_html_script(&lineage)
         .map_err(|err| io::Error::other(format!("dag payload serialization: {err}")))?;
@@ -364,6 +418,7 @@ pub fn render_explore(
         cytoscape_js: CYTOSCAPE_JS,
         cytoscape_dagre_js: CYTOSCAPE_DAGRE_JS,
         explore_lineage_js: EXPLORE_LINEAGE_JS,
+        explore_cte_js: EXPLORE_CTE_JS,
         favicon_data_uri: FAVICON_DATA_URI,
         dag_json: &dag_json,
         model_count: lineage.nodes.len(),
@@ -384,6 +439,7 @@ pub fn render_explore(
         models: &models_pod,
         model_count: models_pod.len(),
         test_count,
+        explore_tests_js: EXPLORE_TESTS_JS,
         payload_json: &payload_json,
     }
     .render()
@@ -711,6 +767,152 @@ mod tests {
         let _ = fs::remove_dir_all(&dir);
     }
 
+    // ----- cte_dags_by_model (cute-dbt#102) ---------------------------
+
+    /// A compiled model whose SQL carries one CTE — the smallest shape
+    /// that yields a non-empty [`DagPayload`].
+    fn cte_model(id: &str) -> Node {
+        model(
+            id,
+            Some("with src_orders as (select * from db.sch.orders) select * from src_orders"),
+            &[],
+        )
+    }
+
+    #[test]
+    fn cte_dags_map_carries_one_entry_per_cte_bearing_model() {
+        let current = manifest_of(vec![
+            cte_model("model.shop.dim_orders"),
+            cte_model("model.shop.stg_orders"),
+        ]);
+        let models = all_models(&current);
+        let payload = payload_for(&current, &models);
+        let dags = cte_dags_by_model(&models, &payload);
+        assert_eq!(dags.len(), 2, "one CTE DAG per CTE-bearing model");
+        let dag = dags
+            .get("model.shop.dim_orders")
+            .expect("keyed by full model node id");
+        let names: Vec<&str> = dag.nodes.iter().map(|n| n.id.as_str()).collect();
+        assert!(
+            names.contains(&"src_orders"),
+            "the CTE node rides the map entry: {names:?}",
+        );
+        assert!(
+            dag.nodes.len() >= 2,
+            "the terminal node rides alongside the CTE: {names:?}",
+        );
+    }
+
+    #[test]
+    fn cte_dags_map_skips_uncompiled_and_cteless_models() {
+        let current = manifest_of(vec![
+            // No WITH clause -> empty graph -> no entry.
+            model("model.shop.flat", Some("select 1"), &[]),
+            // Uncompiled (dbt parse) -> fail-open, no entry (the JS
+            // renders the labeled degraded view off `not_compiled`).
+            model("model.shop.parsed_only", None, &[]),
+            cte_model("model.shop.dim_orders"),
+        ]);
+        let models = all_models(&current);
+        let payload = payload_for(&current, &models);
+        let dags = cte_dags_by_model(&models, &payload);
+        assert_eq!(
+            dags.keys().collect::<Vec<_>>(),
+            vec!["model.shop.dim_orders"],
+            "only the CTE-bearing compiled model gets a map entry",
+        );
+    }
+
+    #[test]
+    fn render_explore_dag_embeds_the_cte_carrier_and_view_toggle() {
+        let current = manifest_of(vec![cte_model("model.shop.dim_orders")]);
+        let models = all_models(&current);
+        let payload = payload_for(&current, &models);
+        let dir = tmp_dir("cte-toggle");
+        render_explore(&dir, &current, &models, &payload).expect("explore renders");
+        let dag = fs::read_to_string(dir.join("dag.html")).expect("dag.html");
+        // The carrier embeds the per-model CTE DAG map.
+        assert!(dag.contains("\"cte_dags\":{"), "cte_dags carrier present");
+        assert!(
+            dag.contains("src_orders"),
+            "the CTE node id rides the dag.html carrier",
+        );
+        // The view toggle: lineage arm active, CTE arm gated on a
+        // highlight at render time (selection is a runtime act).
+        assert!(
+            dag.contains("data-view=\"lineage\""),
+            "lineage toggle arm present",
+        );
+        assert!(dag.contains("data-view=\"cte\""), "CTE toggle arm present");
+        // The CTE view host renders hidden — lineage is the boot view.
+        assert!(
+            dag.contains("class=\"cte-view\" hidden"),
+            "the CTE view host starts hidden: {dag}",
+        );
+        // The first-party CTE engine ships on the page.
+        assert!(
+            dag.contains("cute-dbt explore CTE engine v1"),
+            "dag.html embeds the explore CTE engine",
+        );
+        let _ = fs::remove_dir_all(&dir);
+    }
+
+    // ----- tests.html shared unit-test card (cute-dbt#102) ------------
+
+    #[test]
+    fn render_explore_tests_embeds_the_shared_test_card_and_viewer() {
+        let mut current = three_model_manifest();
+        let ut = crate::domain::UnitTest::new(
+            "test_dim_orders",
+            NodeId::new("dim_orders"),
+            Vec::new(),
+            crate::domain::UnitTestExpect::new(serde_json::Value::Null, None, None),
+            None,
+            DependsOn::default(),
+            None,
+            None,
+            None,
+        );
+        let mut unit_tests = StdHashMap::new();
+        unit_tests.insert("unit_test.shop.dim_orders.test_dim_orders".to_owned(), ut);
+        current = Manifest::new(
+            ManifestMetadata::new("v12"),
+            current.nodes().clone(),
+            unit_tests,
+            StdHashMap::new(),
+        );
+        let models = all_models(&current);
+        let payload = payload_for(&current, &models);
+        let dir = tmp_dir("tests-viewer");
+        render_explore(&dir, &current, &models, &payload).expect("explore renders");
+        let tests = fs::read_to_string(dir.join("tests.html")).expect("tests.html");
+        // The shared askama partial (report.html's test card) renders.
+        assert!(
+            tests.contains("class=\"test-section\""),
+            "the shared test-card partial renders on tests.html",
+        );
+        assert!(tests.contains("id=\"test-select\""), "test selector");
+        assert!(
+            tests.contains("class=\"panel-row\""),
+            "the Given/Expected panel pair renders",
+        );
+        // Each listed test wires its id for the viewer.
+        assert!(
+            tests.contains("data-test-id=\"unit_test.shop.dim_orders.test_dim_orders\""),
+            "the index rows carry data-test-id handles",
+        );
+        // The first-party viewer engine ships; no graph engine does.
+        assert!(
+            tests.contains("cute-dbt explore tests viewer v1"),
+            "tests.html embeds the explore tests viewer",
+        );
+        assert!(
+            !tests.contains("The Cytoscape Consortium") && !tests.contains("cytoscapeDagre"),
+            "tests.html embeds NO Cytoscape assets",
+        );
+        let _ = fs::remove_dir_all(&dir);
+    }
+
     #[test]
     fn explore_models_zip_carries_tests_and_badges() {
         let mut current = three_model_manifest();
diff --git a/src/adapters/render.rs b/src/adapters/render.rs
index e80f25b2..a69ba047 100644
--- a/src/adapters/render.rs
+++ b/src/adapters/render.rs
@@ -433,7 +433,7 @@ fn check_spec_payload(id: HeuristicId) -> CheckSpecPayload {
 }
 
 /// One DAG node — stable id, display label, and role.
-#[derive(Debug, Clone, Serialize)]
+#[derive(Debug, Clone, PartialEq, Eq, Serialize)]
 pub struct NodePayload {
     /// Stable node id — the key for the DAG (Mermaid node), the
     /// `compiled_sql` map, edge endpoints, and given→node binding. Always
@@ -456,7 +456,7 @@ pub struct NodePayload {
 }
 
 /// One DAG edge — `from` and `to` are the [`NodePayload::id`] strings.
-#[derive(Debug, Clone, Serialize)]
+#[derive(Debug, Clone, PartialEq, Eq, Serialize)]
 pub struct EdgePayload {
     /// Source node id (the [`NodePayload::id`] the edge starts from).
     pub from: String,
@@ -469,7 +469,7 @@ pub struct EdgePayload {
 }
 
 /// The full DAG carried in a [`ModelPayload`].
-#[derive(Debug, Clone, Serialize)]
+#[derive(Debug, Clone, PartialEq, Eq, Serialize)]
 pub struct DagPayload {
     /// CTE nodes plus the terminal model node, in stable rendering
     /// order.
diff --git a/templates/explore-cte.js b/templates/explore-cte.js
new file mode 100644
index 00000000..909f39d2
--- /dev/null
+++ b/templates/explore-cte.js
@@ -0,0 +1,274 @@
+/* cute-dbt explore CTE engine v1 (cute-dbt#102)
+   ----------------------------------------------------------------------------
+   The CTE <-> model view toggle on explore's dag.html plus the per-model
+   Cytoscape CTE DAG it renders. Binding decision (epic cute-dbt#99 V3):
+   the CTE view follows the HIGHLIGHTED model — the same in-page selection
+   the click / fuzzy-search-select affordance drives (a Space focus commit
+   implies a highlight, so a committed model is always viewable). With no
+   highlight the CTE arm is disabled; while the CTE view is active a
+   search-select retargets it in place, and a cleared highlight falls back
+   to the lineage view.
+
+   View-state contract (the cute-dbt#102 AC): switching views is LOCAL
+   STATE on the same page — no reload, and the lineage Cytoscape instance
+   is NEVER rebuilt (its pan / zoom / highlight survive a round trip; only
+   cy.resize() runs after un-hiding). The CTE instance rebuilds only on a
+   model retarget — a view change, the cyto-dag.js model-switch precedent;
+   per-interaction work inside a built instance stays in-place.
+
+   Data: the `explore-dag-data` carrier's `cte_dags` map (full model node
+   id -> the SAME DagPayload the report renders for that model:
+   role-classified nodes + join-typed edges, parsed once in Rust). A
+   missing entry on a `not_compiled` model renders the labeled fail-open
+   degraded view (never an error); missing on a compiled model renders
+   the "no CTE structure" sparse state.
+
+   Init hygiene (the ADR-4-amendment contract, explore-page variant):
+   - node labels are CANVAS TEXT — XSS-safe by construction; hostile
+     manifest-derived names draw as glyphs, never parse as HTML.
+   - explicit non-webfont system fontFamily (zero-egress: no font fetch).
+   - the dagre layout runs IN-THREAD via the vendored cytoscape-dagre UMD
+     already registered for the lineage view (never the EPL
+     cytoscape-elk) and NO workers.
+   - measured node widths via canvas measureText (no deprecated
+     `width: label`, no custom wheelSensitivity — both emit console
+     warnings the headless gate rejects).
+   - handlers are bound from THIS file; DOM strings land via textContent
+     only; this file never writes data-selected-model (the Space commit
+     in explore-lineage.js stays the single write site).
+
+   First-party, NOT vendored: lives at templates/explore-cte.js, embedded
+   at compile time via asset_embed::EXPLORE_CTE_JS (include_str!) and
+   interpolated inline by the askama renderer. Banner-pin +
+   end-of-file-sentinel tests in src/adapters/asset_embed.rs guard the
+   include. */
+(function () {
+  "use strict";
+
+  var carrier = document.getElementById("explore-dag-data");
+  if (!carrier) return;
+  var data = JSON.parse(carrier.textContent);
+  if (!data.nodes || !data.nodes.length) return; // empty manifest: no views
+  var cteDags = data.cte_dags || {};
+
+  var toggle = document.querySelector(".view-toggle");
+  var lineageView = document.querySelector(".lineage-view");
+  var cteView = document.querySelector(".cte-view");
+  if (!toggle || !lineageView || !cteView) return;
+  var btnLineage = toggle.querySelector('[data-view="lineage"]');
+  var btnCte = toggle.querySelector('[data-view="cte"]');
+  var host = cteView.querySelector(".cte-canvas");
+  var titleModel = cteView.querySelector(".cte-view-model");
+  var degraded = cteView.querySelector(".cte-degraded");
+  var sparse = cteView.querySelector(".cte-view-empty");
+
+  // id -> lineage node (bare name + the fail-open not_compiled flag).
+  // Prototype-less so a hostile model id can never collide with a
+  // built-in prototype property (the cyto-dag.js precedent).
+  var modelById = Object.create(null);
+  data.nodes.forEach(function (n) { modelById[n.id] = n; });
+
+  var view = "lineage";
+  var highlightedId = null;
+  var cy = null;                // the CTE instance (rebuilt per retarget)
+  var renderedModelId = null;
+
+  // ---- style (canvas text, measured widths, role + join vocabulary) ------
+  var FONT_STACK = 'ui-monospace, SFMono-Regular, Menlo, Consolas, monospace';
+  var measureCtx = document.createElement("canvas").getContext("2d");
+  measureCtx.font = "13px " + FONT_STACK;
+  function labelWidth(label) {
+    return Math.min(300, Math.ceil(measureCtx.measureText(label).width) + 26);
+  }
+
+  // The join-type edge label: the DagPayload wire key with underscores
+  // opened up (`union_all` -> `union all`).
+  function joinLabel(etype) {
+    return String(etype || "from").replace(/_/g, " ");
+  }
+
+  // Explore-page light palette, role vocabulary aligned with the report
+  // (final / import / transform) and the lineage view's hues.
+  var ROLES = {
+    final: { fill: "#e8f1f8", stroke: "#0072B2", shape: "hexagon" },
+    import: { fill: "#eef7ee", stroke: "#1f8a5b", shape: "round-rectangle" },
+    transform: { fill: "#f4f4f5", stroke: "#6b6b76", shape: "rectangle" }
+  };
+
+  function roleStyle(role) {
+    var r = ROLES[role] || ROLES.transform;
+    return {
+      "background-color": r.fill,
+      "border-color": r.stroke,
+      "shape": r.shape
+    };
+  }
+
+  function styleSheet() {
+    return [
+      { selector: "node", style: {
+        "label": "data(label)",
+        "text-valign": "center",
+        "text-halign": "center",
+        "font-family": FONT_STACK,
+        "font-size": 13,
+        "color": "#1c1c1f",
+        "text-wrap": "ellipsis",
+        "text-max-width": 280,
+        "width": "data(w)",
+        "height": 30,
+        "border-width": 1.6,
+        "background-color": ROLES.transform.fill,
+        "border-color": ROLES.transform.stroke,
+        "shape": "rectangle"
+      }},
+      { selector: 'node[role = "import"]', style: roleStyle("import") },
+      { selector: 'node[role = "final"]', style: roleStyle("final") },
+      { selector: "edge", style: {
+        "curve-style": "bezier",
+        "width": 1.8,
+        "line-color": "#8b8b96",
+        "target-arrow-shape": "triangle",
+        "target-arrow-color": "#8b8b96",
+        "arrow-scale": 1.1,
+        "label": "data(elabel)",
+        "font-family": FONT_STACK,
+        "font-size": 10,
+        "color": "#555",
+        "text-rotation": "autorotate",
+        "text-background-color": "#fcfcfd",
+        "text-background-opacity": 1,
+        "text-background-padding": "2px"
+      }},
+      { selector: 'edge[etype = "union_all"], edge[etype = "union_distinct"]', style: {
+        "line-style": "dashed",
+        "line-dash-pattern": [6, 3]
+      }}
+    ];
+  }
+
+  // ---- elements off one cte_dags DagPayload entry --------------------------
+  function buildElements(dag) {
+    var els = [];
+    dag.nodes.forEach(function (n) {
+      var label = String(n.label || n.id);
+      els.push({
+        group: "nodes",
+        // Resolved only via cy.getElementById — a selector-hostile CTE
+        // alias is inert (the cute-dbt#155 / #180 precedent).
+        data: {
+          id: n.id,
+          label: label,
+          w: labelWidth(label),
+          role: n.role || "transform"
+        }
+      });
+    });
+    (dag.edges || []).forEach(function (e, i) {
+      els.push({
+        group: "edges",
+        data: {
+          id: "e" + i,
+          source: e.from,
+          target: e.to,
+          etype: e.edge_type || "from",
+          elabel: joinLabel(e.edge_type)
+        }
+      });
+    });
+    return els;
+  }
+
+  // ---- CTE render (per-model; a view change, so a rebuild is allowed) -----
+  function destroyCte() {
+    if (cy) { cy.destroy(); cy = null; }
+  }
+
+  function renderCte(modelId) {
+    renderedModelId = modelId;
+    var m = modelById[modelId];
+    titleModel.textContent = m ? m.name : String(modelId);
+    host.hidden = false;
+    degraded.hidden = true;
+    sparse.hidden = true;
+    destroyCte();
+    var dag = Object.prototype.hasOwnProperty.call(cteDags, modelId)
+      ? cteDags[modelId]
+      : null;
+    if (!dag) {
+      host.hidden = true;
+      if (m && m.not_compiled) {
+        // Fail-open: the labeled degraded view, never an error.
+        degraded.textContent = m.name + " has no compiled SQL in this manifest"
+          + " (dbt parse) — run dbt compile to fill in its CTE DAG."
+          + " The model still renders in the lineage view.";
+        degraded.hidden = false;
+      } else {
+        sparse.hidden = false;
+      }
+      return;
+    }
+    cy = window.cytoscape({
+      container: host,
+      elements: buildElements(dag),
+      style: styleSheet(),
+      // Same vendored dagre left-to-right ranks as the lineage view —
+      // the one registered layout extension on this page.
+      layout: { name: "dagre", rankDir: "LR", nodeSep: 18, rankSep: 90, edgeSep: 12, fit: true, padding: 24 },
+      minZoom: 0.2,
+      maxZoom: 2.5,
+      boxSelectionEnabled: false
+    });
+  }
+
+  // ---- the view toggle (chrome + selection persist; same page) ------------
+  function setView(next) {
+    if (next === view) return;
+    if (next === "cte" && !highlightedId) return; // gated on a highlight
+    view = next;
+    var isCte = view === "cte";
+    lineageView.hidden = isCte;
+    cteView.hidden = !isCte;
+    btnLineage.classList.toggle("is-active", !isCte);
+    btnLineage.setAttribute("aria-pressed", String(!isCte));
+    btnCte.classList.toggle("is-active", isCte);
+    btnCte.setAttribute("aria-pressed", String(isCte));
+    if (isCte) {
+      if (renderedModelId !== highlightedId) {
+        renderCte(highlightedId);
+      } else if (cy) {
+        cy.resize(); // dimensions only — pan/zoom persist
+      }
+    } else if (window.CuteExploreLineage) {
+      // The lineage instance was never rebuilt: its pan/zoom/highlight
+      // persist; only the canvas dimensions need a refresh.
+      var lcy = window.CuteExploreLineage.cyInstance();
+      if (lcy) lcy.resize();
+    }
+  }
+
+  // The lineage engine's page-local highlight event gates the CTE arm
+  // and retargets an active CTE view in place.
+  document.addEventListener("cute-explore-highlight", function (ev) {
+    highlightedId = ev.detail ? ev.detail.id : null;
+    btnCte.disabled = !highlightedId;
+    if (view !== "cte") return;
+    if (!highlightedId) {
+      setView("lineage");
+      return;
+    }
+    if (highlightedId !== renderedModelId) renderCte(highlightedId);
+  });
+
+  btnLineage.addEventListener("click", function () { setView("lineage"); });
+  btnCte.addEventListener("click", function () { setView("cte"); });
+
+  // Public seam: the headless suites drive + observe the toggle through
+  // this (the window.CuteExploreLineage precedent).
+  window.CuteExploreCte = {
+    activeView: function () { return view; },
+    cyInstance: function () { return cy; },
+    renderedModelId: function () { return renderedModelId; }
+  };
+})();
+/* end of cute-dbt explore CTE engine v1 (cute-dbt#102) */
diff --git a/templates/explore-dag.html b/templates/explore-dag.html
index dea47137..edefb4fd 100644
--- a/templates/explore-dag.html
+++ b/templates/explore-dag.html
@@ -33,6 +33,21 @@
 .lineage-legend { color: #555; font-size: 0.85rem; margin-top: 0.5rem; }
 .lineage-legend .legend-chip { display: inline-block; padding: 0 0.4rem; border: 1.5px solid #0072B2; border-radius: 4px; background: #e8f1f8; color: #1c1c1f; }
 .lineage-legend .legend-chip.notcompiled { border-color: #b07400; border-style: dashed; background: #f4f4f5; }
+/* cute-dbt#102 — the CTE ⇄ model view toggle + the CTE view host. */
+.view-toggle { display: inline-flex; border: 1px solid #c5c5cc; border-radius: 6px; overflow: hidden; }
+.view-toggle button { border: none; border-radius: 0; margin: 0; background: #fff; color: #1c1c1f; padding: 0.25rem 0.7rem; font-size: 0.85rem; cursor: pointer; }
+.view-toggle button + button { border-left: 1px solid #c5c5cc; }
+.view-toggle button.is-active { background: #e8f1f8; font-weight: 600; }
+.view-toggle button:disabled { color: #999; background: #f4f4f5; cursor: not-allowed; }
+.cte-canvas { height: min(70vh, 40rem); border: 1px solid #c5c5cc; border-radius: 6px; background: #fcfcfd; }
+.cte-canvas:focus { outline: 2px solid #0072B2; outline-offset: 2px; }
+.cte-view-title { color: #555; font-size: 0.9rem; margin: 0 0 0.4rem; }
+.cte-degraded, .cte-view-empty { color: #555; font-style: italic; }
+.cte-legend { color: #555; font-size: 0.85rem; margin-top: 0.5rem; }
+.cte-legend .legend-chip { display: inline-block; padding: 0 0.4rem; border-radius: 4px; color: #1c1c1f; }
+.cte-legend .legend-chip.final { border: 1.5px solid #0072B2; background: #e8f1f8; }
+.cte-legend .legend-chip.import { border: 1.5px solid #1f8a5b; background: #eef7ee; }
+.cte-legend .legend-chip.transform { border: 1.5px solid #6b6b76; background: #f4f4f5; }
 </style>
 </head>
 <body>
@@ -56,8 +71,20 @@ <h1>Model lineage</h1>
       <ul class="lineage-search-results" id="lineage-search-results" role="listbox"
           aria-label="Matching models" hidden></ul>
     </div>
-    <p class="lineage-hint">click or search-select highlights a model&rsquo;s lineage &middot; <kbd>Space</kbd> commits focus on the highlighted model</p>
+    {# cute-dbt#102 — the CTE ⇄ model view toggle. The CTE arm is gated
+       on a highlight (disabled at render time; explore-cte.js enables it
+       when a model is highlighted and binds the CTE view to it). #}
+    <div class="view-toggle" role="group" aria-label="Graph view">
+      <button type="button" data-view="lineage" class="is-active" aria-pressed="true">Model lineage</button>
+      <button type="button" data-view="cte" aria-pressed="false" disabled>CTE view</button>
+    </div>
+    <p class="lineage-hint">click or search-select highlights a model&rsquo;s lineage &middot; <kbd>Space</kbd> commits focus &middot; a highlighted model unlocks its CTE view</p>
   </div>
+  {# cute-dbt#102 — the two view hosts. explore-cte.js flips `hidden`
+     between them; the lineage Cytoscape instance is never rebuilt, so
+     its pan/zoom/highlight persist across toggles (local state, same
+     page, no reload). #}
+  <div class="lineage-view">
   {# The canvas host is FOCUSABLE (tabindex) — a search-select moves focus
      here so the follow-up Space lands on the document handler, never in
      the search box (the cute-dbt#101 hard AC). #}
@@ -68,6 +95,23 @@ <h1>Model lineage</h1>
     <span class="legend-chip notcompiled">not compiled</span>
     &mdash; a dashed node has no compiled SQL in this manifest (<code>dbt parse</code>); run <code>dbt compile</code> to fill it in. The explorer renders it anyway (fail-open).
   </div>
+  </div>
+  {# cute-dbt#102 — the CTE view host (hidden until the toggle opens it).
+     A not_compiled model renders the labeled fail-open degraded view in
+     .cte-degraded — never an error; a compiled CTE-less model renders
+     the .cte-view-empty sparse state. #}
+  <div class="cte-view" hidden>
+    <p class="cte-view-title">CTE DAG &mdash; <code class="cte-view-model"></code></p>
+    <div class="cte-canvas" tabindex="0" aria-label="CTE dependency DAG"></div>
+    <p class="cte-degraded" hidden></p>
+    <p class="cte-view-empty" hidden>No CTE DAG available &mdash; this model&rsquo;s compiled SQL has no CTE structure.</p>
+    <div class="cte-legend">
+      <span class="legend-chip final">final select</span>
+      <span class="legend-chip import">import CTE</span>
+      <span class="legend-chip transform">transform CTE</span>
+      &mdash; edges are labeled with their join type.
+    </div>
+  </div>
 </section>
 
 <script type="application/json" id="explore-dag-data">{{ dag_json|safe }}</script>
@@ -94,5 +138,14 @@ <h1>Model lineage</h1>
    Banner-pin + end-of-file sentinel tests guard the include. #}
 {{ explore_lineage_js|safe }}
 </script>
+<script>
+{# cute-dbt#102 — the first-party explore CTE engine (the CTE ⇄ model
+   view toggle + the per-model Cytoscape CTE DAG), embedded from
+   templates/explore-cte.js via asset_embed::EXPLORE_CTE_JS. Parses
+   AFTER the lineage engine so the highlight event + the
+   window.CuteExploreLineage seam it consumes already exist. Banner-pin
+   + end-of-file sentinel tests guard the include. #}
+{{ explore_cte_js|safe }}
+</script>
 </body>
 </html>
diff --git a/templates/explore-lineage.js b/templates/explore-lineage.js
index 8909b49e..59add19b 100644
--- a/templates/explore-lineage.js
+++ b/templates/explore-lineage.js
@@ -157,9 +157,20 @@
   // ---- HIGHLIGHT (click / search-select; in-place, never a commit) --------
   var highlighted = null;
 
+  // cute-dbt#102 — page-local highlight observer hook: the CTE-view
+  // engine (explore-cte.js) gates + retargets its view off this event.
+  // It is NOT the external-drive signal: data-selected-model stays
+  // Space-commit-only (the one write site below).
+  function notifyHighlight(id) {
+    document.dispatchEvent(
+      new CustomEvent("cute-explore-highlight", { detail: { id: id } })
+    );
+  }
+
   function clearHighlight() {
     cy.elements().removeClass("dim sel trace");
     highlighted = null;
+    notifyHighlight(null);
   }
 
   function highlightNode(node) {
@@ -171,6 +182,7 @@
       node.removeClass("dim").addClass("sel");
     });
     highlighted = node;
+    notifyHighlight(node.id());
   }
 
   // ---- FOCUS COMMIT (Space only — the one selectedModel write site) -------
diff --git a/templates/explore-tests.html b/templates/explore-tests.html
index 9f8fac00..3cecadb1 100644
--- a/templates/explore-tests.html
+++ b/templates/explore-tests.html
@@ -9,10 +9,11 @@
 {{ sakura_css|safe }}
 </style>
 <style>
-{# cute-dbt#100 — first-party explore-page chrome. This page is a
-   server-rendered static index (no Mermaid, no DataTables, no JS): the
-   page-aware liveness oracle for it is plain DOM facts. The full
-   interactive unit-test viewer is the epic #99 V3 slice. #}
+{# cute-dbt#100 — first-party explore-page chrome. Since cute-dbt#102
+   the page carries the unit-test VIEWER (the shared test-card partial +
+   the explore-tests.js engine) above the server-rendered per-model
+   index; it still embeds no Mermaid, no DataTables, no jQuery and no
+   graph engine. #}
 body { max-width: 72rem; }
 .explore-header { display: flex; align-items: baseline; gap: 1rem; flex-wrap: wrap; }
 .explore-header h1 { margin-bottom: 0.25rem; }
@@ -23,11 +24,39 @@
 .model-path { color: #555; font-size: 0.85rem; margin: 0 0 0.4rem; }
 .not-compiled-badge { font-size: 0.7em; vertical-align: middle; padding: 0.1rem 0.45rem; border: 1.5px dashed #b07400; border-radius: 4px; background: #f4f4f5; color: #1c1c1f; }
 .explore-tests { margin-bottom: 0.5rem; }
-.explore-test .test-name { font-weight: 600; }
 .explore-test .test-shape { color: #555; font-size: 0.85rem; }
 .explore-test .test-description { color: #555; font-size: 0.9rem; margin: 0.1rem 0 0; }
 .no-tests { color: #555; font-style: italic; }
 .explore-empty { color: #555; font-style: italic; }
+/* cute-dbt#102 — explore-local styling for the SHARED test-card partial
+   (report.html styles the same markup through its chassis CSS, which
+   this light page deliberately does not embed). */
+.explore-viewer { border-top: 1px solid #ddd; padding-top: 0.75rem; margin-top: 0.75rem; }
+.explore-viewer > h2 { margin-bottom: 0.4rem; }
+.test-card { border: 1px solid #c5c5cc; border-radius: 6px; padding: 0.75rem 1rem; background: #fcfcfd; }
+.test-card-head { display: flex; align-items: baseline; gap: 1rem; flex-wrap: wrap; }
+.test-select-field label { font-weight: 600; margin-right: 0.4rem; }
+/* Explore is full-manifest by design: there is no updated/context split,
+   so the partial's scope toggle is inert chrome here — hidden, not
+   forked out of the shared markup. */
+.test-mode-toggle { display: none; }
+.test-badges .tag-badge { display: inline-block; font-size: 0.75rem; color: #1c1c1f; border: 1px solid #c5c5cc; border-radius: 4px; padding: 0 0.35rem; background: #f4f4f5; margin-right: 0.25rem; }
+.test-description { color: #333; margin: 0.5rem 0 0; }
+.test-defined-in { color: #555; font-size: 0.85rem; margin: 0.3rem 0 0; }
+.panel-row { display: flex; gap: 1rem; flex-wrap: wrap; margin-top: 0.75rem; }
+.panel { flex: 1 1 22rem; min-width: 0; border: 1px solid #c5c5cc; border-radius: 6px; padding: 0.6rem 0.8rem; background: #fcfcfd; }
+.panel-header { display: flex; align-items: baseline; gap: 0.6rem; }
+.panel-header h2 { font-size: 1.1rem; margin: 0 0 0.4rem; }
+.table-header { display: flex; align-items: baseline; gap: 0.6rem; flex-wrap: wrap; }
+.table-title { margin: 0.4rem 0 0.2rem; font-size: 0.95rem; }
+.row-count-badge, .format-badge, .this-badge { font-size: 0.75rem; color: #555; border: 1px solid #c5c5cc; border-radius: 4px; padding: 0 0.35rem; background: #f4f4f5; }
+.fixture-provenance { font-size: 0.8rem; color: #555; }
+table.given-table, table.expected-table { font-size: 0.85rem; margin: 0.3rem 0 0.6rem; }
+.cell-null { color: #888; font-style: italic; }
+.empty-hint, .given-empty { color: #555; font-style: italic; }
+.sql-block { font-size: 0.85rem; }
+.test-jump { background: none; border: none; padding: 0; color: #1d7484; font: inherit; font-weight: 600; cursor: pointer; text-decoration: underline; }
+.test-jump:hover, .test-jump:focus { color: #144f5a; }
 </style>
 </head>
 <body>
@@ -45,14 +74,25 @@ <h1>Unit tests</h1>
 {% if models.is_empty() %}
 <p class="explore-empty">No models in this manifest.</p>
 {% endif %}
+{# cute-dbt#102 — the unit-test viewer: the SHARED test-card partial
+   (templates/partials/test-card.html — the exact markup report.html
+   renders) plus the explore-tests.js engine below, which fills it from
+   the embedded cute-dbt-data payload. Hidden when the manifest carries
+   no unit tests (the index's empty states still tell the story). #}
+<section class="explore-viewer" aria-label="Unit-test viewer"{% if test_count == 0 %} hidden{% endif %}>
+<h2>Unit-test viewer</h2>
+{% include "partials/test-card.html" %}
+</section>
 {% for m in models %}
 <section class="explore-model" data-model-id="{{ m.id }}" aria-label="Model {{ m.name }}">
   <h2>{{ m.name }}{% if m.not_compiled %} <span class="not-compiled-badge">not compiled</span>{% endif %}</h2>
   {% match m.path %}{% when Some with (p) %}<p class="model-path"><code>{{ p }}</code></p>
   {% when None %}{% endmatch %}{% if m.tests.is_empty() %}<p class="no-tests">0 unit tests wired</p>
   {% else %}<ul class="explore-tests">
-    {% for t in m.tests %}<li class="explore-test">
-      <span class="test-name">{{ t.name }}</span>
+    {% for t in m.tests %}<li class="explore-test" data-test-id="{{ t.id }}">
+      {# cute-dbt#102 — the test name is a jump button: explore-tests.js
+         selects this test in the viewer above. #}
+      <button type="button" class="test-jump" data-test-id="{{ t.id }}">{{ t.name }}</button>
       <span class="test-shape">&mdash; {{ t.shape }}</span>
       {% match t.description %}{% when Some with (d) %}<p class="test-description">{{ d }}</p>
       {% when None %}{% endmatch %}
@@ -69,5 +109,13 @@ <h2>{{ m.name }}{% if m.not_compiled %} <span class="not-compiled-badge">not com
    carrier id so payload-consuming tooling reads both surfaces the same
    way; the V3 unit-test viewer renders from it. #}
 <script type="application/json" id="cute-dbt-data">{{ payload_json|safe }}</script>
+<script>
+{# cute-dbt#102 — the first-party explore tests viewer (selector
+   population, given/expected fixture grids off the Rust FixtureTable
+   POD, index-row jump wiring), embedded from templates/explore-tests.js
+   via asset_embed::EXPLORE_TESTS_JS. Banner-pin + end-of-file sentinel
+   tests guard the include. #}
+{{ explore_tests_js|safe }}
+</script>
 </body>
 </html>
diff --git a/templates/explore-tests.js b/templates/explore-tests.js
new file mode 100644
index 00000000..d2bf6501
--- /dev/null
+++ b/templates/explore-tests.js
@@ -0,0 +1,267 @@
+/* cute-dbt explore tests viewer v1 (cute-dbt#102)
+   ----------------------------------------------------------------------------
+   The unit-test viewer on explore's tests.html: renders the selected
+   test's description, badges, given fixtures and expected table into the
+   SHARED test-card partial (templates/partials/test-card.html — the same
+   markup report.html renders), reading the embedded `cute-dbt-data`
+   ReportPayload (the build_payload reuse seam).
+
+   Deliberately a LIGHT sibling of the report's interaction engine, not a
+   copy: no jQuery, no DataTables, no diff toggles (explore is
+   full-manifest — there is no changed-set and no PR diff to tint), no
+   Mermaid/Cytoscape. The Current-view fixture grids render the SAME
+   Rust-computed FixtureTable POD ({display, key} cells, cute-dbt#138)
+   the report renders, so the two surfaces cannot drift on cell
+   semantics.
+
+   Affordances:
+   - the test selector (the partial's #test-select) lists every unit
+     test, optgrouped by model;
+   - each index row's test-name button (data-test-id) selects that test
+     in the viewer;
+   - NULL / absent cells keep the report's vocabulary (.cell-null /
+     .cell-absent); sql-format fixtures render as a code block; external
+     fixture files surface the provenance note instead of a silently
+     empty grid (the cute-dbt#126 contract).
+
+   DOM discipline: every dynamic string lands via createElement +
+   textContent — never an HTML-string sink (the asset_embed banner test
+   pins this). First-party, NOT vendored: lives at templates/explore-tests.js,
+   embedded via asset_embed::EXPLORE_TESTS_JS (include_str!). Banner-pin
+   + end-of-file-sentinel tests guard the include. */
+(function () {
+  "use strict";
+
+  var carrier = document.getElementById("cute-dbt-data");
+  var viewer = document.querySelector(".explore-viewer");
+  var select = document.getElementById("test-select");
+  if (!carrier || !viewer || !select) return;
+  var data = JSON.parse(carrier.textContent);
+
+  // Flat id -> {model, test} index over the payload (prototype-less so a
+  // hostile test id can never collide with a built-in property).
+  var byId = Object.create(null);
+  var total = 0;
+  (data.models || []).forEach(function (m) {
+    (m.tests || []).forEach(function (t) {
+      byId[t.id] = { model: m, test: t };
+      total += 1;
+    });
+  });
+  if (!total) {
+    viewer.hidden = true;
+    return;
+  }
+
+  // ---- tiny DOM helpers (textContent only) --------------------------------
+  function el(tag, cls, text) {
+    var node = document.createElement(tag);
+    if (cls) node.className = cls;
+    if (text !== undefined) node.textContent = text;
+    return node;
+  }
+
+  function clear(node) {
+    while (node.firstChild) node.removeChild(node.firstChild);
+  }
+
+  function rowsText(n) {
+    return n + " row" + (n === 1 ? "" : "s");
+  }
+
+  // ---- fixture-shape predicates (the interaction.js vocabulary) -----------
+  function isSqlCodeBlock(obj) {
+    return Boolean(obj && obj.format === "sql" && typeof obj.rows === "string");
+  }
+
+  function isExternalFixture(obj) {
+    return Boolean(obj && obj.fixture && (obj.rows === null || obj.rows === undefined));
+  }
+
+  function isLoadedExternalFixture(obj) {
+    return Boolean(obj && obj.fixture && obj.rows !== null && obj.rows !== undefined);
+  }
+
+  function provenanceChip(name) {
+    var chip = el("span", "fixture-provenance", "from ");
+    chip.appendChild(el("code", "", String(name)));
+    return chip;
+  }
+
+  function externalNote(name) {
+    var box = el("div", "given-empty external-fixture-note",
+      "data in external fixture file: ");
+    box.appendChild(el("code", "", String(name)));
+    return box;
+  }
+
+  function sqlBlock(text) {
+    var pre = el("pre", "sql-block");
+    pre.appendChild(el("code", "", String(text)));
+    return pre;
+  }
+
+  // ---- the Current-view grid off the Rust FixtureTable POD ----------------
+  function cellTd(cell) {
+    var td = document.createElement("td");
+    var key = cell && cell.key;
+    if (!key || key.t === "null") {
+      td.className = "cell-null";
+      td.textContent = "NULL";
+      return td;
+    }
+    if (key.t === "absent") {
+      td.className = "cell-absent";
+      return td;
+    }
+    if (key.t === "number") td.className = "cell-num";
+    td.textContent = cell.display;
+    return td;
+  }
+
+  function buildTable(table, cls) {
+    var tbl = el("table", cls);
+    var thead = document.createElement("thead");
+    var hr = document.createElement("tr");
+    (table.columns || []).forEach(function (c) {
+      hr.appendChild(el("th", "", c));
+    });
+    thead.appendChild(hr);
+    tbl.appendChild(thead);
+    var tbody = document.createElement("tbody");
+    (table.rows || []).forEach(function (r) {
+      var tr = document.createElement("tr");
+      (r.cells || []).forEach(function (cell) {
+        tr.appendChild(cellTd(cell));
+      });
+      tbody.appendChild(tr);
+    });
+    tbl.appendChild(tbody);
+    return tbl;
+  }
+
+  // ---- per-test render -----------------------------------------------------
+  function renderGiven(g) {
+    var sec = el("section", "given-section");
+    var hdr = el("div", "table-header");
+    hdr.appendChild(el("h4", "table-title", "given · " + g.input));
+    if (g.is_this) hdr.appendChild(el("span", "this-badge", "prior model state"));
+    if (isLoadedExternalFixture(g)) hdr.appendChild(provenanceChip(g.fixture));
+    if (isSqlCodeBlock(g)) {
+      hdr.appendChild(el("span", "format-badge", "format: sql"));
+      sec.appendChild(hdr);
+      sec.appendChild(sqlBlock(g.rows));
+      return sec;
+    }
+    if (isExternalFixture(g)) {
+      if (g.format) hdr.appendChild(el("span", "format-badge", "format: " + g.format));
+      sec.appendChild(hdr);
+      sec.appendChild(externalNote(g.fixture));
+      return sec;
+    }
+    var table = g.table || { columns: [], rows: [] };
+    if (g.format && g.format !== "dict") {
+      hdr.appendChild(el("span", "format-badge", "format: " + g.format));
+    }
+    hdr.appendChild(el("span", "row-count-badge", rowsText(table.rows.length)));
+    sec.appendChild(hdr);
+    sec.appendChild(buildTable(table, "given-table"));
+    return sec;
+  }
+
+  function renderExpected(t) {
+    var body = document.querySelector(".expected-body");
+    var rowcount = document.querySelector(".expected-rowcount");
+    clear(body);
+    if (isLoadedExternalFixture(t.expected)) {
+      body.appendChild(provenanceChip(t.expected.fixture));
+    }
+    if (isSqlCodeBlock(t.expected)) {
+      rowcount.textContent = "format: sql";
+      body.appendChild(sqlBlock(t.expected.rows));
+      return;
+    }
+    if (isExternalFixture(t.expected)) {
+      rowcount.textContent = "external fixture";
+      body.appendChild(externalNote(t.expected.fixture));
+      return;
+    }
+    var table = (t.expected && t.expected.table) || { columns: [], rows: [] };
+    rowcount.textContent = rowsText(table.rows.length);
+    body.appendChild(buildTable(table, "expected-table"));
+  }
+
+  function renderTest(t) {
+    // Description (the partial's hidden-when-absent contract).
+    var desc = document.querySelector(".test-description");
+    if (t.description) {
+      desc.textContent = t.description;
+      desc.hidden = false;
+    } else {
+      desc.textContent = "";
+      desc.hidden = true;
+    }
+    // Badges: tag chips (kept light — explore has no diff badges).
+    var badges = document.querySelector(".test-badges");
+    clear(badges);
+    (t.tags || []).forEach(function (tag) {
+      badges.appendChild(el("span", "tag-badge", tag));
+    });
+    // Details body: where the test was authored.
+    var details = document.querySelector(".test-details-body");
+    clear(details);
+    if (t.defined_in) {
+      var p = el("p", "test-defined-in", "defined in ");
+      p.appendChild(el("code", "", t.defined_in));
+      details.appendChild(p);
+    }
+    // Given panel.
+    var givenWrap = document.querySelector(".left-panel-body");
+    clear(givenWrap);
+    if (!t.given || !t.given.length) {
+      givenWrap.appendChild(el("div", "empty-hint", "No fixtures defined for this test."));
+    } else {
+      t.given.forEach(function (g) { givenWrap.appendChild(renderGiven(g)); });
+    }
+    // Expected panel.
+    renderExpected(t);
+  }
+
+  function selectTest(id) {
+    var entry = byId[id];
+    if (!entry) return;
+    if (select.value !== id) select.value = id;
+    renderTest(entry.test);
+  }
+
+  // ---- selector population + wiring ----------------------------------------
+  (data.models || []).forEach(function (m) {
+    if (!m.tests || !m.tests.length) return;
+    var og = document.createElement("optgroup");
+    og.label = m.name;
+    m.tests.forEach(function (t) {
+      var opt = document.createElement("option");
+      opt.value = t.id;
+      opt.textContent = t.name;
+      og.appendChild(opt);
+    });
+    select.appendChild(og);
+  });
+
+  select.addEventListener("change", function () { selectTest(select.value); });
+
+  // Index rows: each test-name button jumps the viewer to its test.
+  Array.prototype.forEach.call(
+    document.querySelectorAll(".test-jump[data-test-id]"),
+    function (btn) {
+      btn.addEventListener("click", function () {
+        selectTest(btn.getAttribute("data-test-id"));
+        if (viewer.scrollIntoView) viewer.scrollIntoView({ block: "start" });
+      });
+    }
+  );
+
+  // Boot: the first test in payload order.
+  selectTest(select.value);
+})();
+/* end of cute-dbt explore tests viewer v1 (cute-dbt#102) */
diff --git a/templates/partials/test-card.html b/templates/partials/test-card.html
new file mode 100644
index 00000000..167f387e
--- /dev/null
+++ b/templates/partials/test-card.html
@@ -0,0 +1,39 @@
+<section class="test-section" aria-label="Unit test">
+  <div class="test-card">
+    <div class="test-card-head">
+      <div class="selector-field test-select-field">
+        <label for="test-select">Unit test</label>
+        <select id="test-select"></select>
+      </div>
+      <div class="test-mode-toggle" role="group" aria-label="Test scope" data-testid="updated-toggle">
+        <button type="button" data-test-mode="updated" class="is-active" aria-pressed="true">Updated only</button>
+        <button type="button" data-test-mode="all" aria-pressed="false">All tests</button>
+      </div>
+      <div class="test-badges"></div>
+    </div>
+    <p class="test-description" hidden></p>
+    <div class="test-details-body"></div>
+  </div>
+</section>
+
+<div class="panel-row">
+
+  <section class="panel left-panel" aria-label="Given inputs">
+    {# cute-dbt#201 — the Inspect/All-inputs segmented toggle is retired:
+       the left panel is the Given panel, always rendering every given
+       input (node detail moved to the DAG shelf above). #}
+    <div class="panel-header">
+      <h2>Given</h2>
+    </div>
+    <div class="left-panel-body" data-mode="inputs"></div>
+  </section>
+
+  <section class="panel expected-panel" aria-label="Expected output">
+    <div class="panel-header">
+      <h2>Expected</h2>
+      <span class="row-count-badge expected-rowcount">0 rows</span>
+    </div>
+    <div class="expected-body"></div>
+  </section>
+
+</div>
diff --git a/templates/report.html b/templates/report.html
index 3cd31095..849839d4 100644
--- a/templates/report.html
+++ b/templates/report.html
@@ -285,46 +285,14 @@ <h2>CTE dependency DAG</h2>
    authoring-YAML drawer inside .test-details-body stays collapsible. The
    description <p> replaces the retired test-description-section: the #74
    no-empty-landmark intent carries over via the `hidden` attribute the JS
-   toggles on description presence. #}
-<section class="test-section" aria-label="Unit test">
-  <div class="test-card">
-    <div class="test-card-head">
-      <div class="selector-field test-select-field">
-        <label for="test-select">Unit test</label>
-        <select id="test-select"></select>
-      </div>
-      <div class="test-mode-toggle" role="group" aria-label="Test scope" data-testid="updated-toggle">
-        <button type="button" data-test-mode="updated" class="is-active" aria-pressed="true">Updated only</button>
-        <button type="button" data-test-mode="all" aria-pressed="false">All tests</button>
-      </div>
-      <div class="test-badges"></div>
-    </div>
-    <p class="test-description" hidden></p>
-    <div class="test-details-body"></div>
-  </div>
-</section>
-
-<div class="panel-row">
-
-  <section class="panel left-panel" aria-label="Given inputs">
-    {# cute-dbt#201 — the Inspect/All-inputs segmented toggle is retired:
-       the left panel is the Given panel, always rendering every given
-       input (node detail moved to the DAG shelf above). #}
-    <div class="panel-header">
-      <h2>Given</h2>
-    </div>
-    <div class="left-panel-body" data-mode="inputs"></div>
-  </section>
-
-  <section class="panel expected-panel" aria-label="Expected output">
-    <div class="panel-header">
-      <h2>Expected</h2>
-      <span class="row-count-badge expected-rowcount">0 rows</span>
-    </div>
-    <div class="expected-body"></div>
-  </section>
-
-</div>
+   toggles on description presence. Since cute-dbt#102 the card + the
+   Given/Expected panel pair live in templates/partials/test-card.html —
+   a shared askama partial reused VERBATIM by explore's tests.html (the
+   V3 viewer); the include is output-preserving (askama strips the
+   partial's final newline, so the blank line below restores the one
+   that separated the panel row from the payload carrier) — this
+   report's bytes are unchanged, gated by the byte-identity golden. #}
+{% include "partials/test-card.html" %}
 
 <script type="application/json" id="cute-dbt-data">{{ payload_json|safe }}</script>
 

From f56a080f17175925f1b1936f7bb9dc81356f16d8 Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Thu, 11 Jun 2026 01:32:00 -0400
Subject: [PATCH 2/3] test: BDD explore_view_toggle scenarios + headless
 CTE-toggle and tests-viewer gates (#102)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

features/explore_view_toggle.feature + its step module assert the
render-time surface: the gated toggle DOM, the per-model cte_dags
carrier (present for CTE-bearing models, absent for uncompiled — the
fail-open contract), the shared test-card partial on tests.html, the
index-row viewer wiring, the no-Cytoscape posture and the resource-ref
zero-egress scan. ExploreModelDecl grows compiled_sql so scenarios can
author a WITH clause.

The headless suite gains two real-Chromium file:// tests: the CTE/model
toggle (disabled-until-highlight, CTE render off the carrier, lineage
state persistence across the round trip, the labeled degraded view,
console-clean + zero external requests) and the tests.html viewer
(selector population, FixtureTable grid with the NULL-cell vocabulary,
expected row count, index jump wiring, no cytoscape global). The
committed-pages liveness oracle now also asserts the viewer booted.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
---
 features/explore_view_toggle.feature |  75 +++++
 tests/headless_zero_egress.rs        | 443 ++++++++++++++++++++++++++-
 tests/steps/explore_full_manifest.rs |   7 +-
 tests/steps/explore_view_toggle.rs   | 207 +++++++++++++
 tests/steps/mod.rs                   |   1 +
 tests/steps/world.rs                 |   4 +
 6 files changed, 728 insertions(+), 9 deletions(-)
 create mode 100644 features/explore_view_toggle.feature
 create mode 100644 tests/steps/explore_view_toggle.rs

diff --git a/features/explore_view_toggle.feature b/features/explore_view_toggle.feature
new file mode 100644
index 00000000..bacbaad6
--- /dev/null
+++ b/features/explore_view_toggle.feature
@@ -0,0 +1,75 @@
+# Maps: cute-dbt#102 — the explore view toggle (CTE ⇄ model) on dag.html
+# and the tests.html unit-test viewer (epic cute-dbt#99 V3).
+#
+# dag.html: the toolbar gains a two-arm view toggle. The lineage arm is
+# the boot view; the CTE arm is GATED on a highlighted model (disabled at
+# render time — selection is a runtime act) and renders that model's CTE
+# DAG with the same vendored Cytoscape + dagre engine as the lineage
+# view. The carrier's `cte_dags` map ships one DagPayload per
+# CTE-bearing compiled model — the SAME role-classified, join-typed
+# graph the report renders (the build_payload reuse seam). An uncompiled
+# model ships NO entry: the client renders the labeled fail-open
+# degraded view off the lineage node's not_compiled flag, never an
+# error, and PreflightError keeps its four variants.
+#
+# tests.html: the unit-test viewer renders through the SHARED askama
+# partial (templates/partials/test-card.html) — the exact test-card +
+# Given/Expected markup report.html renders (the include is
+# output-preserving there, gated by the byte-identity goldens). The page
+# embeds NO Cytoscape, no dagre, no Mermaid, no DataTables and no
+# jQuery; the explore-tests.js engine fills the card from the embedded
+# cute-dbt-data payload, and each index row wires its test id so a click
+# selects it in the viewer.
+#
+# Scenarios are self-contained subprocess wire round-trips (the
+# explore_full_manifest.rs pattern): Givens accumulate a synthetic
+# manifest plan, the When runs the real `cute-dbt explore` subprocess,
+# and the Thens assert emitted-page + payload facts. The RUNTIME toggle
+# interaction (click-to-enable, view flip, selection persistence) is
+# exercised by the headless Chromium suite
+# (tests/headless_zero_egress.rs), which these render-time assertions
+# complement, not replace.
+Feature: explore's dag.html toggles between model lineage and a CTE view, and tests.html serves the unit-test viewer
+
+  Background:
+    Given an explore scenario
+
+  @no-baseline-usage-error
+  Scenario: dag.html renders the view toggle with the CTE arm gated on selection
+    Given the explore manifest declares the model "orders"
+    When I run cute-dbt explore on the synthetic manifest
+    Then the exit code is 0
+    And dag.html renders the lineage and CTE view toggle arms
+    And dag.html renders the CTE view host hidden at render time
+    And dag.html embeds the explore CTE engine
+
+  @no-baseline-usage-error
+  Scenario: The dag carrier embeds a CTE DAG per CTE-bearing model and none for an uncompiled one
+    Given the explore manifest declares the model "dim_orders"
+    And the explore model "dim_orders" compiles to SQL with the CTE "src_orders"
+    And the explore manifest declares the model "mart_orders"
+    And the explore model "mart_orders" has no compiled SQL
+    When I run cute-dbt explore on the synthetic manifest
+    Then the exit code is 0
+    And the dag carrier embeds a CTE DAG for "dim_orders" containing the node "src_orders"
+    And the dag carrier embeds no CTE DAG for "mart_orders"
+    And dag.html marks "mart_orders" as not compiled
+
+  @no-baseline-usage-error
+  Scenario: tests.html renders the shared unit-test card and wires the index to the viewer
+    Given the explore manifest declares the model "dim_orders"
+    And the explore model "dim_orders" declares unit test "test_dim_orders_grain"
+    When I run cute-dbt explore on the synthetic manifest
+    Then the exit code is 0
+    And tests.html renders the shared unit-test card
+    And tests.html embeds the explore tests viewer
+    And tests.html wires the unit test "test_dim_orders_grain" to the viewer
+
+  @no-baseline-usage-error
+  Scenario: tests.html embeds no graph engine and keeps the zero-egress invariant
+    Given the explore manifest declares the model "dim_orders"
+    And the explore model "dim_orders" declares unit test "test_dim_orders_grain"
+    When I run cute-dbt explore on the synthetic manifest
+    Then the exit code is 0
+    And tests.html embeds no Cytoscape engine
+    And tests.html carries no external resource references
diff --git a/tests/headless_zero_egress.rs b/tests/headless_zero_egress.rs
index 1f98b695..384a0d30 100644
--- a/tests/headless_zero_egress.rs
+++ b/tests/headless_zero_egress.rs
@@ -419,6 +419,22 @@ fn every_committed_explore_page_makes_zero_external_requests_when_opened_via_fil
                      does not parse to a non-empty models array.",
                 ));
             }
+            // cute-dbt#102 — the unit-test viewer booted: explore-tests.js
+            // populated the shared partial's selector from the payload
+            // (the playground fixture carries unit tests).
+            let viewer_ok = eval(
+                &tab,
+                "document.querySelectorAll('#test-select option').length",
+            )
+            .as_u64()
+            .unwrap_or(0)
+                > 0;
+            if !viewer_ok {
+                failures.push(format!(
+                    "examples/{filename}: the unit-test viewer did not populate \
+                     #test-select — explore-tests.js failed to boot offline.",
+                ));
+            }
         }
 
         let captured = external.lock().unwrap().clone();
@@ -450,14 +466,15 @@ fn every_committed_explore_page_makes_zero_external_requests_when_opened_via_fil
 // (a probe into OUR OWN generated page inside a hermetic headless test)
 // — not JS `eval()` over untrusted input.
 
-/// A synthetic compiled model node with explicit `depends_on.nodes`
-/// edges — the in-process explore-page harness's only builder.
-fn explore_model(id: &str, deps: &[&str]) -> Node {
+/// A synthetic model node with explicit `depends_on.nodes` edges and an
+/// explicit compiled body (`None` = the fail-open `dbt parse` shape) —
+/// the in-process explore-page harness's base builder.
+fn explore_node(id: &str, deps: &[&str], compiled: Option<&str>) -> Node {
     Node::new(
         NodeId::new(id),
         "model",
         Checksum::new("sha256", "ck"),
-        Some("select 1".to_owned()),
+        compiled.map(str::to_owned),
         None,
         DependsOn::new(Vec::new(), deps.iter().map(|d| NodeId::new(*d)).collect()),
         None,
@@ -467,14 +484,23 @@ fn explore_model(id: &str, deps: &[&str]) -> Node {
     )
 }
 
-/// Render an explore page in-process (the headless fixture discipline:
+/// A synthetic compiled model node (`select 1` body — no CTE structure).
+fn explore_model(id: &str, deps: &[&str]) -> Node {
+    explore_node(id, deps, Some("select 1"))
+}
+
+/// Render the explore pages in-process (the headless fixture discipline:
 /// domain objects -> `render_explore`, no subprocess) and return the
-/// `file://` URL of the emitted `dag.html`.
-fn render_explore_dag(stem: &str, nodes: Vec<Node>) -> String {
+/// out directory. `unit_tests` is keyed by manifest unit-test id.
+fn render_explore_pages(
+    stem: &str,
+    nodes: Vec<Node>,
+    unit_tests: HashMap<String, cute_dbt::domain::UnitTest>,
+) -> PathBuf {
     let manifest = Manifest::new(
         ManifestMetadata::new("v12"),
         nodes.into_iter().map(|n| (n.id().clone(), n)).collect(),
-        HashMap::new(),
+        unit_tests,
         HashMap::new(),
     );
     let models = all_models(&manifest);
@@ -491,6 +517,13 @@ fn render_explore_dag(stem: &str, nodes: Vec<Node>) -> String {
     let dir = PathBuf::from(env!("CARGO_TARGET_TMPDIR")).join(stem);
     let _ = std::fs::remove_dir_all(&dir);
     render_explore(&dir, &manifest, &models, &payload).expect("explore renders");
+    dir
+}
+
+/// Render an explore page in-process and return the `file://` URL of
+/// the emitted `dag.html`.
+fn render_explore_dag(stem: &str, nodes: Vec<Node>) -> String {
+    let dir = render_explore_pages(stem, nodes, HashMap::new());
     let p = dir.join("dag.html");
     format!("file://{}", p.to_str().expect("page path is valid UTF-8"))
 }
@@ -896,6 +929,400 @@ fn explore_dag_canvas_labels_stay_xss_safe_and_highlight_cost_is_subframe() {
     let _ = tab.close(true);
 }
 
+// ===== cute-dbt#102 — the CTE ⇄ model view toggle + the tests.html =====
+// ===== unit-test viewer                                            =====
+
+#[test]
+#[ignore = "requires Chrome; runs explicitly in the headless-zero-egress CI job via `-- --ignored`"]
+fn explore_dag_cte_toggle_renders_cte_view_and_preserves_lineage_state() {
+    // cute-dbt#102 — the CTE ⇄ model view toggle, driven end to end:
+    //   1. boot: the CTE arm is DISABLED (no highlight yet).
+    //   2. a search-select highlight enables it.
+    //   3. clicking the CTE arm renders the highlighted model's CTE DAG
+    //      with the page's Cytoscape + dagre engine (nodes + the
+    //      join-typed edge off the cte_dags carrier).
+    //   4. toggling back to lineage reveals the SAME lineage instance —
+    //      its highlight classes survived (chrome + selection persist;
+    //      local state, same page, no reload).
+    //   5. highlighting the uncompiled model and re-entering the CTE
+    //      view renders the labeled fail-open degraded view — never an
+    //      error.
+    // Riders: zero console warnings/errors and zero external requests
+    // for the whole session.
+    let cte_sql = "with src_orders as (select * from db.sch.raw_orders) \
+                   select * from src_orders";
+    let url = render_explore_dag(
+        "explore-cte-toggle",
+        vec![
+            explore_node("model.shop.dim_orders", &[], Some(cte_sql)),
+            explore_model("model.shop.stg_orders", &[]),
+            // The fail-open witness: no compiled SQL (dbt parse).
+            explore_node("model.shop.mart_orders", &["model.shop.dim_orders"], None),
+        ],
+    );
+
+    let browser = launch_browser();
+    let tab = browser.new_tab().expect("new tab");
+
+    // Console + network recorders, subscribed BEFORE navigate.
+    tab.call_method(Runtime::Enable(None))
+        .expect("enable Runtime domain");
+    tab.call_method(headless_chrome::protocol::cdp::Log::Enable(None))
+        .expect("enable Log domain");
+    let console_noise = Arc::new(Mutex::new(Vec::<String>::new()));
+    let console_recorder = console_noise.clone();
+    tab.call_method(Network::Enable {
+        max_total_buffer_size: None,
+        max_resource_buffer_size: None,
+        max_post_data_size: None,
+        report_direct_socket_traffic: None,
+        enable_durable_messages: None,
+    })
+    .expect("enable Network domain");
+    let external = Arc::new(Mutex::new(Vec::<ExternalRequest>::new()));
+    let external_recorder = external.clone();
+    tab.add_event_listener(Arc::new(move |event: &Event| match event {
+        Event::RuntimeConsoleAPICalled(e) => {
+            use headless_chrome::protocol::cdp::Runtime::ConsoleAPICalledEventTypeOption as T;
+            if matches!(e.params.Type, T::Warning | T::Error) {
+                let text = e
+                    .params
+                    .args
+                    .first()
+                    .and_then(|a| {
+                        a.description
+                            .clone()
+                            .or_else(|| a.value.as_ref().map(ToString::to_string))
+                    })
+                    .unwrap_or_default();
+                console_recorder
+                    .lock()
+                    .unwrap()
+                    .push(format!("console.{:?}: {text}", e.params.Type));
+            }
+        }
+        Event::LogEntryAdded(e) => {
+            use headless_chrome::protocol::cdp::Log::LogEntryLevel as L;
+            if matches!(e.params.entry.level, L::Warning | L::Error) {
+                console_recorder.lock().unwrap().push(format!(
+                    "log.{:?}: {}",
+                    e.params.entry.level, e.params.entry.text
+                ));
+            }
+        }
+        Event::NetworkRequestWillBeSent(e) => {
+            let req_url = e.params.request.url.clone();
+            if scheme_is_external(&req_url) {
+                external_recorder.lock().unwrap().push(ExternalRequest {
+                    url: req_url,
+                    initiator_type: format!("{:?}", e.params.initiator.Type),
+                    initiator_url: e.params.initiator.url.clone(),
+                    initiator_line: e.params.initiator.line_number,
+                });
+            }
+        }
+        _ => {}
+    }))
+    .expect("subscribe console + network events");
+
+    tab.navigate_to(&url).expect("navigate to file:// URL");
+    tab.wait_until_navigated().expect("await navigation");
+    tab.wait_for_element_with_custom_timeout(".lineage-canvas canvas", Duration::from_secs(15))
+        .expect("the lineage Cytoscape canvas boots offline");
+
+    // --- 1. boot: the CTE arm is gated --------------------------------------
+    assert_eq!(
+        eval(
+            &tab,
+            "document.querySelector('.view-toggle [data-view=\"cte\"]').disabled"
+        ),
+        serde_json::Value::Bool(true),
+        "the CTE arm starts disabled — no model is highlighted yet",
+    );
+
+    // --- 2. a search-select highlight enables it ------------------------------
+    let _ = eval(
+        &tab,
+        "document.querySelector('.lineage-search-input').focus()",
+    );
+    tab.type_str("dim").expect("type the query");
+    tab.press_key("Enter").expect("select the top match");
+    assert_eq!(
+        eval(&tab, "window.CuteExploreLineage.highlightedId()"),
+        serde_json::Value::String("model.shop.dim_orders".to_owned()),
+        "search-select highlights dim_orders",
+    );
+    assert_eq!(
+        eval(
+            &tab,
+            "document.querySelector('.view-toggle [data-view=\"cte\"]').disabled"
+        ),
+        serde_json::Value::Bool(false),
+        "the highlight unlocks the CTE arm",
+    );
+
+    // --- 3. the CTE view renders the highlighted model's CTE DAG --------------
+    let _ = eval(
+        &tab,
+        "document.querySelector('.view-toggle [data-view=\"cte\"]').click()",
+    );
+    tab.wait_for_element_with_custom_timeout(
+        ".cte-view .cte-canvas canvas",
+        Duration::from_secs(15),
+    )
+    .expect("the CTE Cytoscape canvas renders offline");
+    assert_eq!(
+        eval(&tab, "window.CuteExploreCte.activeView()"),
+        serde_json::Value::String("cte".to_owned()),
+        "the active view is the CTE view",
+    );
+    assert_eq!(
+        eval(&tab, "window.CuteExploreCte.renderedModelId()"),
+        serde_json::Value::String("model.shop.dim_orders".to_owned()),
+        "the CTE view binds to the HIGHLIGHTED model",
+    );
+    assert_eq!(
+        eval(
+            &tab,
+            "JSON.stringify([window.CuteExploreCte.cyInstance().nodes().length, \
+              window.CuteExploreCte.cyInstance().edges().length])"
+        ),
+        serde_json::Value::String("[2,1]".to_owned()),
+        "the CTE DAG carries the src_orders CTE + the terminal and one edge",
+    );
+    assert_eq!(
+        eval(&tab, "document.querySelector('.lineage-view').hidden"),
+        serde_json::Value::Bool(true),
+        "the lineage host hides while the CTE view is active (same page)",
+    );
+
+    // --- 4. toggling back preserves the lineage instance + highlight ----------
+    let _ = eval(
+        &tab,
+        "document.querySelector('.view-toggle [data-view=\"lineage\"]').click()",
+    );
+    assert_eq!(
+        eval(&tab, "document.querySelector('.lineage-view').hidden"),
+        serde_json::Value::Bool(false),
+        "the lineage view returns",
+    );
+    assert_eq!(
+        eval(
+            &tab,
+            "window.CuteExploreLineage.cyInstance()\
+               .getElementById('model.shop.dim_orders').hasClass('sel')"
+        ),
+        serde_json::Value::Bool(true),
+        "the lineage highlight SURVIVES the round trip — the instance \
+         was never rebuilt (selection persists)",
+    );
+
+    // --- 5. the uncompiled model renders the labeled degraded view ------------
+    let _ = eval(
+        &tab,
+        "document.querySelector('.lineage-search-input').focus()",
+    );
+    let _ = eval(
+        &tab,
+        "document.querySelector('.lineage-search-input').value = ''",
+    );
+    tab.type_str("mart").expect("type the second query");
+    tab.press_key("Enter").expect("select the uncompiled model");
+    let _ = eval(
+        &tab,
+        "document.querySelector('.view-toggle [data-view=\"cte\"]').click()",
+    );
+    assert_eq!(
+        eval(&tab, "document.querySelector('.cte-degraded').hidden"),
+        serde_json::Value::Bool(false),
+        "an uncompiled model shows the labeled fail-open degraded view",
+    );
+    let degraded = eval(&tab, "document.querySelector('.cte-degraded').textContent");
+    assert!(
+        degraded
+            .as_str()
+            .is_some_and(|t| t.contains("mart_orders") && t.contains("dbt compile")),
+        "the degraded view names the model + the remediation: {degraded:?}",
+    );
+    assert_eq!(
+        eval(&tab, "document.querySelector('.cte-canvas').hidden"),
+        serde_json::Value::Bool(true),
+        "no canvas pretends to be a DAG on the degraded view",
+    );
+
+    // --- riders: console-clean + zero egress ----------------------------------
+    let noise = console_noise.lock().unwrap().clone();
+    assert!(
+        noise.is_empty(),
+        "the toggle session must emit zero console warnings/errors; got:\n{}",
+        noise.join("\n"),
+    );
+    let captured = external.lock().unwrap().clone();
+    assert!(
+        captured.is_empty(),
+        "the toggle session must make zero external requests; got:\n{}",
+        captured
+            .iter()
+            .map(ToString::to_string)
+            .collect::<Vec<_>>()
+            .join("\n"),
+    );
+
+    let _ = tab.close(true);
+}
+
+#[test]
+#[ignore = "requires Chrome; runs explicitly in the headless-zero-egress CI job via `-- --ignored`"]
+fn explore_tests_viewer_renders_fixture_grids_offline() {
+    // cute-dbt#102 — the tests.html unit-test viewer: the shared
+    // test-card partial filled by explore-tests.js from the embedded
+    // payload. Proof points: the selector populates, the given grid
+    // renders the Rust FixtureTable POD (incl. the NULL-cell
+    // vocabulary), the expected row count lands, and the index row's
+    // jump button drives the viewer. Riders: zero console noise, zero
+    // external requests.
+    use cute_dbt::domain::{UnitTest, UnitTestExpect, UnitTestGiven};
+
+    let given = UnitTestGiven::new(
+        "ref('stg_orders')",
+        serde_json::json!([
+            {"id": 1, "name": "a"},
+            {"id": 2, "name": null}
+        ]),
+        Some("dict".to_owned()),
+        None,
+    );
+    let ut = UnitTest::new(
+        "test_dim_orders_grain",
+        NodeId::new("dim_orders"),
+        vec![given],
+        UnitTestExpect::new(serde_json::json!([{"id": 1}]), None, None),
+        Some("one row per order".to_owned()),
+        DependsOn::default(),
+        None,
+        None,
+        None,
+    );
+    let mut unit_tests = HashMap::new();
+    unit_tests.insert(
+        "unit_test.shop.dim_orders.test_dim_orders_grain".to_owned(),
+        ut,
+    );
+    let dir = render_explore_pages(
+        "explore-tests-viewer",
+        vec![
+            explore_model("model.shop.dim_orders", &[]),
+            explore_model("model.shop.stg_orders", &[]),
+        ],
+        unit_tests,
+    );
+    let p = dir.join("tests.html");
+    let url = format!("file://{}", p.to_str().expect("page path is valid UTF-8"));
+
+    let browser = launch_browser();
+    let tab = browser.new_tab().expect("new tab");
+    tab.call_method(Network::Enable {
+        max_total_buffer_size: None,
+        max_resource_buffer_size: None,
+        max_post_data_size: None,
+        report_direct_socket_traffic: None,
+        enable_durable_messages: None,
+    })
+    .expect("enable Network domain");
+    let external = Arc::new(Mutex::new(Vec::<ExternalRequest>::new()));
+    let external_recorder = external.clone();
+    tab.add_event_listener(Arc::new(move |event: &Event| {
+        if let Event::NetworkRequestWillBeSent(e) = event {
+            let req_url = e.params.request.url.clone();
+            if scheme_is_external(&req_url) {
+                external_recorder.lock().unwrap().push(ExternalRequest {
+                    url: req_url,
+                    initiator_type: format!("{:?}", e.params.initiator.Type),
+                    initiator_url: e.params.initiator.url.clone(),
+                    initiator_line: e.params.initiator.line_number,
+                });
+            }
+        }
+    }))
+    .expect("subscribe Network.requestWillBeSent");
+
+    tab.navigate_to(&url).expect("navigate to file:// URL");
+    tab.wait_until_navigated().expect("await navigation");
+
+    // The selector populated from the payload.
+    assert_eq!(
+        eval(
+            &tab,
+            "document.querySelectorAll('#test-select option').length"
+        ),
+        serde_json::Value::from(1u64),
+        "the unit-test selector lists the one declared test",
+    );
+    // The given grid renders the FixtureTable POD: 2 rows x 2 columns,
+    // with the NULL cell in the report's vocabulary.
+    assert_eq!(
+        eval(
+            &tab,
+            "document.querySelectorAll('.left-panel-body table.given-table tbody td').length"
+        ),
+        serde_json::Value::from(4u64),
+        "the given grid renders 2x2 cells",
+    );
+    assert_eq!(
+        eval(
+            &tab,
+            "document.querySelector('.left-panel-body td.cell-null').textContent"
+        ),
+        serde_json::Value::String("NULL".to_owned()),
+        "a null fixture value renders the NULL cell affordance",
+    );
+    // The expected panel's row count.
+    assert_eq!(
+        eval(
+            &tab,
+            "document.querySelector('.expected-rowcount').textContent"
+        ),
+        serde_json::Value::String("1 row".to_owned()),
+        "the expected row count lands in the panel header",
+    );
+    // The description landed and is visible.
+    assert_eq!(
+        eval(&tab, "document.querySelector('.test-description').hidden"),
+        serde_json::Value::Bool(false),
+        "the authored description is visible",
+    );
+    // The index row's jump button drives the viewer (same test here —
+    // the click must keep the card coherent, not throw).
+    let _ = eval(
+        &tab,
+        "document.querySelector('.test-jump[data-test-id]').click()",
+    );
+    assert_eq!(
+        eval(&tab, "document.getElementById('test-select').value"),
+        serde_json::Value::String("unit_test.shop.dim_orders.test_dim_orders_grain".to_owned()),
+        "the jump button selects its test in the viewer",
+    );
+    // No graph engine on this page.
+    assert_eq!(
+        eval(&tab, "typeof window.cytoscape"),
+        serde_json::Value::String("undefined".to_owned()),
+        "tests.html ships no Cytoscape global",
+    );
+
+    let captured = external.lock().unwrap().clone();
+    assert!(
+        captured.is_empty(),
+        "the tests.html viewer must make zero external requests; got:\n{}",
+        captured
+            .iter()
+            .map(ToString::to_string)
+            .collect::<Vec<_>>()
+            .join("\n"),
+    );
+
+    let _ = tab.close(true);
+}
+
 /// Evaluate `expr` in the page; panic on a thrown JS exception so a
 /// missing selector can never silently pass the gate.
 fn eval(tab: &headless_chrome::Tab, expr: &str) -> serde_json::Value {
diff --git a/tests/steps/explore_full_manifest.rs b/tests/steps/explore_full_manifest.rs
index 73742fbd..4713400c 100644
--- a/tests/steps/explore_full_manifest.rs
+++ b/tests/steps/explore_full_manifest.rs
@@ -36,6 +36,7 @@ fn declares_model(world: &mut World, bare: String) {
     world.explore_plan.models.push(ExploreModelDecl {
         bare,
         compiled: true,
+        compiled_sql: None,
         deps: Vec::new(),
         tests: Vec::new(),
     });
@@ -75,7 +76,11 @@ fn run_explore_on_synthetic(world: &mut World) {
     let mut manifest = empty_manifest();
     for m in &plan.models {
         let deps: Vec<&str> = m.deps.iter().map(String::as_str).collect();
-        let compiled = m.compiled.then_some("select 1");
+        // cute-dbt#102 — an explicit compiled body (the CTE-view
+        // scenarios author a WITH clause) over the `select 1` default.
+        let compiled = m
+            .compiled
+            .then(|| m.compiled_sql.as_deref().unwrap_or("select 1"));
         manifest = with_node(
             manifest,
             model_node_with_deps(&m.bare, "ck", compiled, &deps),
diff --git a/tests/steps/explore_view_toggle.rs b/tests/steps/explore_view_toggle.rs
new file mode 100644
index 00000000..d2d8a038
--- /dev/null
+++ b/tests/steps/explore_view_toggle.rs
@@ -0,0 +1,207 @@
+//! Step definitions for `features/explore_view_toggle.feature` —
+//! cute-dbt#102, the explore view toggle (CTE ⇄ model) on dag.html and
+//! the tests.html unit-test viewer.
+//!
+//! Reuses the `explore_full_manifest.rs` Givens/When (the synthetic
+//! `ExplorePlan` accumulator + the real `cute-dbt explore` subprocess);
+//! the Thens here assert the cute-dbt#102 render-time surface: the
+//! two-arm view toggle's DOM (CTE arm disabled — selection is a runtime
+//! act), the carrier's per-model `cte_dags` map (present for a
+//! CTE-bearing compiled model, ABSENT for an uncompiled one — the
+//! fail-open contract renders a labeled degraded view client-side,
+//! never an error), the shared test-card partial on tests.html, the
+//! index-row viewer wiring, and the no-graph-engine + zero-egress
+//! posture of the tests page. The RUNTIME toggle behavior (enable on
+//! highlight, view flip, lineage state persistence) is the headless
+//! Chromium suite's job (`tests/headless_zero_egress.rs`).
+
+use cucumber::{given, then};
+use serde_json::Value;
+
+use super::World;
+use super::explore_full_manifest::{lineage_payload, payload_node};
+
+/// The rendered dag.html, panicking with stderr context when absent.
+fn dag_html(world: &World) -> String {
+    world
+        .explore_dag_html
+        .clone()
+        .unwrap_or_else(|| panic!("dag.html was not written; stderr={}", world.last_stderr))
+}
+
+/// The rendered tests.html, panicking with stderr context when absent.
+fn tests_html(world: &World) -> String {
+    world
+        .explore_tests_html
+        .clone()
+        .unwrap_or_else(|| panic!("tests.html was not written; stderr={}", world.last_stderr))
+}
+
+// --- Given ----------------------------------------------------------------
+
+#[given(regex = r#"^the explore model "([^"]+)" compiles to SQL with the CTE "([^"]+)"$"#)]
+fn model_compiles_with_cte(world: &mut World, bare: String, cte: String) {
+    let decl = world
+        .explore_plan
+        .models
+        .iter_mut()
+        .find(|m| m.bare == bare)
+        .unwrap_or_else(|| panic!("model {bare:?} must be declared before it is configured"));
+    decl.compiled_sql = Some(format!(
+        "with {cte} as (select * from db.sch.orders) select * from {cte}"
+    ));
+}
+
+// --- dag.html: the view toggle ----------------------------------------------
+
+#[then("dag.html renders the lineage and CTE view toggle arms")]
+fn dag_renders_view_toggle(world: &mut World) {
+    let html = dag_html(world);
+    let dom = tl::parse(&html, tl::ParserOptions::default()).expect("dag.html must parse");
+    let parser = dom.parser();
+    let arm = |view: &str| {
+        dom.query_selector(&format!("button[data-view=\"{view}\"]"))
+            .and_then(|mut it| it.next())
+            .and_then(|h| h.get(parser))
+            .and_then(|n| n.as_tag())
+            .unwrap_or_else(|| panic!("dag.html must render the {view} toggle arm"))
+            .attributes()
+            .clone()
+    };
+    let lineage = arm("lineage");
+    assert!(
+        lineage.get("disabled").is_none(),
+        "the lineage arm (the boot view) is never disabled",
+    );
+    let cte = arm("cte");
+    assert!(
+        cte.get("disabled").is_some(),
+        "the CTE arm is GATED on a highlight — disabled at render time \
+         (selection is a runtime act)",
+    );
+}
+
+#[then("dag.html renders the CTE view host hidden at render time")]
+fn dag_renders_cte_host_hidden(world: &mut World) {
+    let html = dag_html(world);
+    let dom = tl::parse(&html, tl::ParserOptions::default()).expect("dag.html must parse");
+    let parser = dom.parser();
+    let host = dom
+        .query_selector("div.cte-view")
+        .and_then(|mut it| it.next())
+        .and_then(|h| h.get(parser))
+        .and_then(|n| n.as_tag())
+        .expect("dag.html must render <div class=\"cte-view\">");
+    assert!(
+        host.attributes().get("hidden").is_some(),
+        "the CTE view host starts hidden — lineage is the boot view",
+    );
+}
+
+#[then("dag.html embeds the explore CTE engine")]
+fn dag_embeds_cte_engine(world: &mut World) {
+    let html = dag_html(world);
+    assert!(
+        html.contains("cute-dbt explore CTE engine v1"),
+        "the first-party CTE engine banner must be inlined",
+    );
+}
+
+// --- dag.html: the cte_dags carrier ------------------------------------------
+
+#[then(regex = r#"^the dag carrier embeds a CTE DAG for "([^"]+)" containing the node "([^"]+)"$"#)]
+fn carrier_embeds_cte_dag(world: &mut World, bare: String, cte_node: String) {
+    let payload = lineage_payload(world);
+    let model_id = payload_node(&payload, &bare)["id"]
+        .as_str()
+        .expect("model id is a string")
+        .to_owned();
+    let dag = &payload["cte_dags"][&model_id];
+    assert!(
+        dag.is_object(),
+        "cte_dags must carry an entry for {bare:?} ({model_id}): {payload}",
+    );
+    let nodes = dag["nodes"].as_array().expect("cte dag nodes array");
+    assert!(
+        nodes
+            .iter()
+            .any(|n| n["id"] == Value::String(cte_node.clone())),
+        "the {bare:?} CTE DAG must contain the {cte_node:?} node: {dag}",
+    );
+}
+
+#[then(regex = r#"^the dag carrier embeds no CTE DAG for "([^"]+)"$"#)]
+fn carrier_embeds_no_cte_dag(world: &mut World, bare: String) {
+    let payload = lineage_payload(world);
+    let model_id = payload_node(&payload, &bare)["id"]
+        .as_str()
+        .expect("model id is a string")
+        .to_owned();
+    assert!(
+        payload["cte_dags"].get(&model_id).is_none(),
+        "an uncompiled model ships NO cte_dags entry — the client \
+         renders the labeled fail-open degraded view off not_compiled, \
+         never an error: {payload}",
+    );
+}
+
+// --- tests.html: the shared unit-test card -----------------------------------
+
+#[then("tests.html renders the shared unit-test card")]
+fn tests_html_renders_shared_card(world: &mut World) {
+    let html = tests_html(world);
+    let dom = tl::parse(&html, tl::ParserOptions::default()).expect("tests.html must parse");
+    let parser = dom.parser();
+    for selector in ["section.test-section", "div.panel-row"] {
+        assert!(
+            dom.query_selector(selector)
+                .and_then(|mut it| it.next())
+                .and_then(|h| h.get(parser))
+                .is_some(),
+            "tests.html must render the shared partial's {selector} \
+             (templates/partials/test-card.html — the markup report.html renders)",
+        );
+    }
+    assert!(
+        dom.get_element_by_id("test-select").is_some(),
+        "the partial's unit-test selector must be present",
+    );
+}
+
+#[then("tests.html embeds the explore tests viewer")]
+fn tests_html_embeds_viewer(world: &mut World) {
+    let html = tests_html(world);
+    assert!(
+        html.contains("cute-dbt explore tests viewer v1"),
+        "the first-party tests-viewer banner must be inlined",
+    );
+}
+
+#[then(regex = r#"^tests\.html wires the unit test "([^"]+)" to the viewer$"#)]
+fn tests_html_wires_test(world: &mut World, test: String) {
+    let html = tests_html(world);
+    let handle = format!("data-test-id=\"unit_test.jaffle_shop.{test}\"");
+    assert!(
+        html.contains(&handle),
+        "the index row must carry the {handle} viewer handle",
+    );
+}
+
+#[then("tests.html embeds no Cytoscape engine")]
+fn tests_html_no_cytoscape(world: &mut World) {
+    let html = tests_html(world);
+    assert!(
+        !html.contains("The Cytoscape Consortium"),
+        "tests.html must not embed the Cytoscape core (its license banner leaked)",
+    );
+    assert!(
+        !html.contains("cytoscapeDagre"),
+        "tests.html must not embed the cytoscape-dagre layout extension",
+    );
+}
+
+#[then("tests.html carries no external resource references")]
+fn tests_html_zero_egress(world: &mut World) {
+    let html = tests_html(world);
+    super::super::common::assert_no_external_refs(&html);
+}
diff --git a/tests/steps/mod.rs b/tests/steps/mod.rs
index 5a059546..0f65e9f7 100644
--- a/tests/steps/mod.rs
+++ b/tests/steps/mod.rs
@@ -19,6 +19,7 @@ pub mod diff_scoping;
 pub mod explore_cli;
 pub mod explore_full_manifest;
 pub mod explore_lineage_dag;
+pub mod explore_view_toggle;
 pub mod fail_closed;
 pub mod incremental_models;
 pub mod pr_diff_scoping;
diff --git a/tests/steps/world.rs b/tests/steps/world.rs
index 3dcf35cf..f0a17c94 100644
--- a/tests/steps/world.rs
+++ b/tests/steps/world.rs
@@ -215,6 +215,10 @@ pub struct ExploreModelDecl {
     /// `false` ⇒ `compiled_code: null` (the fail-open "not compiled"
     /// scenario); `true` ⇒ a compiled model.
     pub compiled: bool,
+    /// Explicit compiled SQL for a compiled model (cute-dbt#102 — the
+    /// CTE-view scenarios need a `WITH` clause). `None` ⇒ the default
+    /// `select 1` body (no CTE structure).
+    pub compiled_sql: Option<String>,
     /// Bare names of models this model depends on (lineage edges).
     pub deps: Vec<String>,
     /// Bare names of unit tests targeting this model.

From 88e267d65e96eaa1428c55fb36513c41a4bdf85e Mon Sep 17 00:00:00 2001
From: "github-actions[bot]"
 <41898282+github-actions[bot]@users.noreply.github.com>
Date: Thu, 11 Jun 2026 01:32:01 -0400
Subject: [PATCH 3/3] ci: bump feature-count mirror 17 -> 18 for
 explore_view_toggle (#102)

Both mirrors move atomically: the ci.yml feature-count job and the
lefthook.yml pre-push hook (expected=18), with the history comments
extended.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
---
 .github/workflows/ci.yml | 3 ++-
 lefthook.yml             | 9 +++++----
 2 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index fd1b8495..3326cb64 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -326,6 +326,7 @@ jobs:
     #   - 14 after check_selection (cute-dbt#171)
     #   - 16 after explore_cli + explore_full_manifest (cute-dbt#100)
     #   - 17 after explore_lineage_dag (cute-dbt#101)
+    #   - 18 after explore_view_toggle (cute-dbt#102)
     # The README is not a feature. The job name deliberately carries no
     # number (cute-dbt#68 — the old `==6` display label went stale across
     # several bumps): the enforced count lives ONLY in the `expected=`
@@ -343,7 +344,7 @@ jobs:
       - name: features/*.feature count matches expected
         run: |
           set -euo pipefail
-          expected=17
+          expected=18
           count=$(find features -maxdepth 1 -name '*.feature' | wc -l | tr -d ' ')
           echo "feature-count: expected ${expected}, found ${count}"
           if [ "$count" != "$expected" ]; then
diff --git a/lefthook.yml b/lefthook.yml
index f8b17878..e31c3add 100644
--- a/lefthook.yml
+++ b/lefthook.yml
@@ -89,9 +89,10 @@ pre-push:
     feature-count:
       # Asserts the .feature-count invariant; the enforced count lives ONLY
       # in the `expected=` line below (cute-dbt#68 — numbers in labels and
-      # comments go stale). History: bumped to 17 in cute-dbt#101 when
-      # explore_lineage_dag.feature joined the contract; previously bumped
-      # in cute-dbt#100 (explore_cli + explore_full_manifest),
+      # comments go stale). History: bumped to 18 in cute-dbt#102 when
+      # explore_view_toggle.feature joined the contract; previously bumped
+      # in cute-dbt#101 (explore_lineage_dag),
+      # cute-dbt#100 (explore_cli + explore_full_manifest),
       # cute-dbt#171 (check_selection), cute-dbt#169 (coverage_checks),
       # cute-dbt#145 (incremental_models), cute-dbt#98 (cell_table_diff),
       # cute-dbt#84 (pr_diff_scoping), cute-dbt#71 (consumer_report_contract),
@@ -99,7 +100,7 @@ pre-push:
       # Mirrors the `feature-count` CI job; the README is not a feature.
       run: |
         set -euo pipefail
-        expected=17
+        expected=18
         count=$(find features -maxdepth 1 -name '*.feature' | wc -l | tr -d ' ')
         if [ "$count" != "$expected" ]; then
           echo "feature-count: expected ${expected} .feature files, found ${count}"