diff --git a/README.md b/README.md
index 326f1504..b01631a6 100644
--- a/README.md
+++ b/README.md
@@ -126,15 +126,13 @@ narrow.
   over-report relative to dbt's unrendered-config diff (it never
   under-reports), and dbt's `persisted_descriptions` sub-selector has no
   cute-dbt modifier yet.
-- **`source()` references are not bound to fixtures.** dbt resolves
-  `source('package', 'name')` to a relation name at `dbt compile`
-  time, so the compiled SQL the renderer sees no longer carries the
-  `source()` form — only the resolved relation. Binding a unit-test
-  `given: source(...)` to its import-CTE node requires reading the
-  manifest's `sources` block and re-resolving on the renderer side.
-  Tracked:
-  [`cute-dbt#57`](https://github.com/breezy-bays-labs/cute-dbt/issues/57)
-  → v0.2 sources widening.
+- **`source()` givens bind via the dominant authored form only.** The
+  given-input parsers accept dbt's serialized single-quoted positional
+  form (`source('a', 'b')`, `ref('name')`, whitespace/keyword-case
+  tolerant). The engine-valid but rare double-quoted and
+  `name=`/`table_name=` keyword-argument variants are deliberately not
+  parsed — an unparsed given simply stays unbound (the empty-state
+  copy), never an error.
 
 ## Import-CTE binding
 
@@ -165,6 +163,23 @@ case-insensitive:
      single CTE node. Tracked:
      [`cute-dbt#34`](https://github.com/breezy-bays-labs/cute-dbt/issues/34).
 
+A `given: source('a', 'b')` input takes one extra resolution hop before
+the same two-pass match
+([`cute-dbt#57`](https://github.com/breezy-bays-labs/cute-dbt/issues/57)):
+dbt resolves `{{ source('a', 'b') }}` to the physical relation at
+`dbt compile` time, so the compiled SQL never carries the literal
+`source(...)` form. cute-dbt therefore resolves the authored
+`(source_name, table)` pair against the manifest's top-level `sources`
+block, takes the entry's physical `identifier` (falling back to the
+last segment of `relation_name`, then to `name` — dbt's identifier
+default), strips identifier quoting, and feeds that token through the
+identical two-pass match above. The lookup runs on the YAML
+`source_name` + `name` (the authored arguments), never on `identifier`
+— an overridden identifier still binds. A pair missing from the
+`sources` block leaves the given unbound — fail-open, same as an
+unresolvable `ref()`; sources need no preflight (they are referenced by
+models, never analyzed themselves).
+
 When neither pass matches — and the node is an `Import` CTE — the
 node-detail panel surfaces *"no fixture provided — dbt treats
 unspecified inputs as empty"*. The same empty-state is the
diff --git a/examples/playground-report.html b/examples/playground-report.html
index 904a5e9a..afefbe8d 100644
--- a/examples/playground-report.html
+++ b/examples/playground-report.html
@@ -1723,7 +1723,7 @@ <h2>Expected</h2>
 
 </div>
 
-<script type="application/json" id="cute-dbt-data">{"baseline":"tests/fixtures/playground-baseline.json","models":[{"name":"dim_payers","path":"models/marts/core/dim_payers.sql","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","authoring_yaml":"  # cute-dbt's authoring-YAML drawer (since #69) attaches contiguous\n  # `#`-comment lines at the SAME indent as `- name:` immediately above\n  # the test to the test's authored slice. This block demonstrates the\n  # LEADING bracket — useful for stating the test's intent before the\n  # reader sees the assertion (cute-dbt#73).\n  - name: test_dim_payers_injects_unknown_sentinel\n    description: |\n      dim_payers UNION-ALLs an unknown-member sentinel row (payer_key = -1)\n      with the sequenced source rows. This test verifies the sentinel\n      survives the union and the sequenced rows are surrogate-keyed\n      starting at 1. Uses dbt's dict format for both GIVEN and EXPECT —\n      dict format only compares listed columns, so non-deterministic\n      outputs (`_loaded_at` via `current_timestamp`) are excluded from\n      assertion automatically.\n    model: dim_payers\n    # The INSIDE bracket — comments at deeper indent than `- name:` ride\n    # along with the body slice as raw text. Cute-dbt preserves them\n    # verbatim in the Authoring YAML drawer (cute-dbt#73).\n    given:\n      - input: ref('stg_synthea__payers')\n        format: dict\n        rows:\n          - payer_id: 'a00000aa-0000-0000-0000-000000000001'\n            payer_name: 'Acme Health'\n            address: '1 Acme Way'\n            city: 'Boston'\n            state: 'MA'\n            zip_code: '02101'\n            phone: '555-0100'\n            amount_covered: 1000.0\n            amount_uncovered: 250.0\n            revenue: 1250.0\n            covered_encounters: 10\n            uncovered_encounters: 2\n            covered_medications: 5\n            uncovered_medications: 1\n            covered_procedures: 3\n            uncovered_procedures: 0\n            covered_immunizations: 4\n            uncovered_immunizations: 0\n            unique_customers: 8\n            average_quality_of_life_score: 0.85\n            member_months: 96\n    expect:\n      format: dict\n      rows:\n        - payer_key: -1\n          payer_id: 'UNKNOWN'\n          payer_name: 'Unknown Payer'\n        - payer_key: 1\n          payer_id: 'a00000aa-0000-0000-0000-000000000001'\n          payer_name: 'Acme Health'\n  # The TRAILING bracket — contiguous `#`-comment lines at the SAME\n  # indent as `- name:`, immediately following the test body and\n  # terminated by EOF or a blank line, are attached to this test's\n  # slice. Useful for cross-references and follow-up notes (cute-dbt#73).","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"}],"suppressed":{"source":"pragma","reason":"unknown_member is a constant sentinel arm, exercised by design"},"pin_node":"final"}]},{"name":"fct_clinical_events","path":"models/marts/core/fct_clinical_events.sql","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_encounters_incremental","path":"models/marts/core/fct_encounters_incremental.sql","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":true,"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","authoring_yaml":"  # cute-dbt#145 — an incremental-model unit test. `overrides.macros.\n  # is_incremental: true` drives the model's is_incremental() branch,\n  # `given: - input: this` supplies the model's prior state, and Expected is\n  # the rows MERGED/INSERTED by the run — not the final table after the merge.\n  - name: test_fct_encounters_incremental_appends_new_encounters\n    description: |\n      fct_encounters_incremental appends encounters newer than the latest\n      already-loaded start_time. With is_incremental() true, only the new\n      encounter (e2) is merged; the prior row (e1, supplied via `this`) is\n      untouched, so Expected is the single inserted row — the materialization\n      delta, not the resulting table.\n    model: fct_encounters_incremental\n    overrides:\n      macros:\n        is_incremental: true\n    given:\n      - input: this\n        format: dict\n        rows:\n          - encounter_id: 'e1'\n            patient_id: 'p1'\n            encounter_type: 'wellness'\n            start_time: '2025-01-01 09:00:00'\n            total_cost: 100.0\n      - input: ref('stg_synthea__encounters')\n        format: dict\n        rows:\n          - encounter_id: 'e1'\n            patient_id: 'p1'\n            encounter_type: 'wellness'\n            start_time: '2025-01-01 09:00:00'\n            total_cost: 100.0\n          - encounter_id: 'e2'\n            patient_id: 'p2'\n            encounter_type: 'emergency'\n            start_time: '2025-02-01 14:30:00'\n            total_cost: 500.0\n    expect:\n      format: dict\n      rows:\n        - encounter_id: 'e2'\n          patient_id: 'p2'\n          encounter_type: 'emergency'\n          start_time: '2025-02-01 14:30:00'\n          total_cost: 500.0","is_incremental_mode":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)"}]},{"name":"int_dq_quarantine__encounters","path":"models/intermediate/quarantine/int_dq_quarantine__encounters.sql","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":"mart_date_state_grid","path":"models/marts/analytics/mart_date_state_grid.sql","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","authoring_yaml":"  # Cross-join demo (cute-dbt#64): mart_date_state_grid's CROSS JOIN\n  # CTE gives cute-dbt's renderer a real cross-join edge to draw. This\n  # test also mixes given formats (dict + csv) in a single unit_test.\n  - name: test_mart_date_state_grid_cross_joins_months_and_states\n    description: |\n      mart_date_state_grid CROSS JOINs the distinct calendar months from\n      dim_date with the distinct non-null patient states from staging.\n      Three daily dim_date rows collapse to two months; four patient\n      rows collapse to two states (one NULL filtered out, one duplicate\n      deduplicated). The result is the full 2 x 2 cartesian product —\n      four grid rows. Mixes a dict given (dim_date) with a csv given\n      (patients) in one test.\n    model: mart_date_state_grid\n    given:\n      - input: ref('dim_date')\n        format: dict\n        rows:\n          - date_actual: 2024-01-15\n            year_actual: 2024\n            month_actual: 1\n            month_name: 'January'\n          - date_actual: 2024-01-16\n            year_actual: 2024\n            month_actual: 1\n            month_name: 'January'\n          - date_actual: 2024-02-01\n            year_actual: 2024\n            month_actual: 2\n            month_name: 'February'\n      - input: ref('stg_synthea__patients')\n        format: csv\n        rows: |\n          patient_id,state\n          a00000aa-0000-0000-0000-000000000001,Massachusetts\n          a00000aa-0000-0000-0000-000000000002,Connecticut\n          a00000aa-0000-0000-0000-000000000003,\n          a00000aa-0000-0000-0000-000000000004,Massachusetts\n    expect:\n      format: csv\n      rows: |\n        month_key,year_actual,month_actual,month_name,state\n        202401,2024,1,January,Massachusetts\n        202401,2024,1,January,Connecticut\n        202402,2024,2,February,Massachusetts\n        202402,2024,2,February,Connecticut","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","table":{"columns":["patient_id","state"],"rows":[{"cells":[{"display":"a00000aa-0000-0000-0000-000000000001","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000001"}},{"display":"Massachusetts","key":{"t":"str","v":"Massachusetts"}}]},{"cells":[{"display":"a00000aa-0000-0000-0000-000000000002","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000002"}},{"display":"Connecticut","key":{"t":"str","v":"Connecticut"}}]},{"cells":[{"display":"a00000aa-0000-0000-0000-000000000003","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000003"}},{"display":"","key":{"t":"null"}}]},{"cells":[{"display":"a00000aa-0000-0000-0000-000000000004","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000004"}},{"display":"Massachusetts","key":{"t":"str","v":"Massachusetts"}}]}]},"rows":[{"patient_id":"a00000aa-0000-0000-0000-000000000001","state":"Massachusetts"},{"patient_id":"a00000aa-0000-0000-0000-000000000002","state":"Connecticut"},{"patient_id":"a00000aa-0000-0000-0000-000000000003","state":null},{"patient_id":"a00000aa-0000-0000-0000-000000000004","state":"Massachusetts"}],"format":"csv","column_meta":{"patient_id":{"description":"Unique patient identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},"state":{"description":"State of residence (full state name, e.g., Massachusetts)"}}}],"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","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","authoring_yaml":"  # LEADING bracket for test 1 — the slicer attaches contiguous\n  # `#`-comment lines at the SAME indent as `- name:` immediately above\n  # the test (no blank-line gap below) to this test's authored slice\n  # (cute-dbt#69 / #73).\n  - name: test_mart_dq_summary_combines_encounter_and_medication_metrics\n    description: |\n      mart_dq_summary UNION-ALLs metrics from stg_synthea__encounters\n      and stg_synthea__medications. This test mocks two encounter rows\n      (one invalid) and two medication rows (both invalid), then asserts\n      the per-entity counts + quarantine rate. Uses csv format for both\n      GIVEN and EXPECT — compact tabular form across many boolean\n      dq-flag columns.\n    model: mart_dq_summary\n    # INSIDE bracket for test 1 — comments at deeper indent than\n    # `- name:` ride along with the body slice as raw text (cute-dbt#69\n    # / #73).\n    given:\n      - input: ref('stg_synthea__encounters')\n        format: csv\n        rows: |\n          is_dq_valid,valid_encounter_timestamps,no_future_encounter_dates,end_after_1900,start_after_1900\n          false,false,true,true,true\n          true,true,true,true,true\n      - input: ref('stg_synthea__medications')\n        format: csv\n        rows: |\n          is_dq_valid,valid_medication_dates,no_future_medication_dates,start_after_1900,end_after_1900_if_present\n          false,false,true,true,true\n          false,true,false,true,true\n    expect:\n      format: csv\n      rows: |\n        entity_type,quarantined_count,total_count,quarantine_rate_pct,failed_timestamp_validations\n        encounters,1,2,50.00,1\n        medications,2,2,100.00,1\n  # TRAILING bracket for test 1 — the comment block butts against the\n  # body above (no blank-line gap) and is terminated below by the blank\n  # line separating the two tests (cute-dbt#69 / #73).","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","authoring_yaml":"  # LEADING bracket for test 2 — sits between the blank-line\n  # terminator above and `- name:` below with no further gap, so the\n  # leading-wins tiebreaker is moot here (cute-dbt#69 / #73).\n  - name: test_mart_dq_summary_zero_quarantined_when_all_valid\n    description: |\n      mart_dq_summary should report zero quarantined_count and 0.00\n      quarantine_rate_pct when every upstream row passes data-quality\n      validations. Uses sql format for the GIVEN mocks and dict format\n      for the EXPECT — dict expects only compare listed columns, so\n      non-deterministic outputs (`_generated_at` from\n      `current_timestamp`) are excluded from comparison.\n    model: mart_dq_summary\n    # INSIDE bracket for test 2 — same rule as test 1 (cute-dbt#69 /\n    # #73). Demonstrates that the slicer ride-along applies to every\n    # unit_test, not just the first in the file.\n    given:\n      - input: ref('stg_synthea__encounters')\n        format: sql\n        rows: |\n          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\n      - input: ref('stg_synthea__medications')\n        format: sql\n        rows: |\n          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\n    expect:\n      format: dict\n      rows:\n        - entity_type: 'encounters'\n          quarantined_count: 0\n          total_count: 1\n          quarantine_rate_pct: 0.00\n        - entity_type: 'medications'\n          quarantined_count: 0\n          total_count: 1\n          quarantine_rate_pct: 0.00\n    overrides:\n      macros:\n        dbt.current_timestamp: \"'2024-01-15 00:00:00'\"\n      vars:\n        dq_quarantine_threshold: 5\n      env_vars:\n        DBT_DQ_REGION: 'us-east-1'\n  # TRAILING bracket for test 2 — terminated by the blank line\n  # separating it from test 3 (cute-dbt#69 / #73).","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__patients","path":"models/staging/synthea/stg_synthea__patients.sql","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","authoring_yaml":"  - name: test_stg_synthea__patients_renames_and_hashes_source_columns\n    description: |\n      stg_synthea__patients renames the raw Synthea UPPERCASE columns to\n      snake_case and hashes the SSN with md5. The given mocks the\n      synthea_raw.patients SOURCE directly (inline dict rows) — the only\n      unit test in this project whose input is a source() rather than a\n      ref() (cute-dbt#57). Dict expect compares listed columns only, so\n      the non-deterministic _loaded_at (current_timestamp) is excluded\n      from assertion automatically.\n    model: stg_synthea__patients\n    given:\n      - input: source('synthea_raw', 'patients')\n        format: dict\n        rows:\n          - Id: 'c0000000-0000-0000-0000-000000000001'\n            FIRST: 'Ada'\n            LAST: 'Lovelace'\n            GENDER: 'F'\n            CITY: 'Boston'\n            STATE: 'Massachusetts'\n            SSN: '999-99-9999'\n    expect:\n      format: dict\n      rows:\n        - patient_id: 'c0000000-0000-0000-0000-000000000001'\n          first_name: 'Ada'\n          last_name: 'Lovelace'\n          gender: 'F'\n          city: 'Boston'\n          state: 'Massachusetts'\n          ssn_hash: '257cf696294931925796925d89aa0afb'","given":[{"input":"source('synthea_raw', 'patients')","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}],"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"},"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 type="application/json" id="cute-dbt-data">{"baseline":"tests/fixtures/playground-baseline.json","models":[{"name":"dim_payers","path":"models/marts/core/dim_payers.sql","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","authoring_yaml":"  # cute-dbt's authoring-YAML drawer (since #69) attaches contiguous\n  # `#`-comment lines at the SAME indent as `- name:` immediately above\n  # the test to the test's authored slice. This block demonstrates the\n  # LEADING bracket — useful for stating the test's intent before the\n  # reader sees the assertion (cute-dbt#73).\n  - name: test_dim_payers_injects_unknown_sentinel\n    description: |\n      dim_payers UNION-ALLs an unknown-member sentinel row (payer_key = -1)\n      with the sequenced source rows. This test verifies the sentinel\n      survives the union and the sequenced rows are surrogate-keyed\n      starting at 1. Uses dbt's dict format for both GIVEN and EXPECT —\n      dict format only compares listed columns, so non-deterministic\n      outputs (`_loaded_at` via `current_timestamp`) are excluded from\n      assertion automatically.\n    model: dim_payers\n    # The INSIDE bracket — comments at deeper indent than `- name:` ride\n    # along with the body slice as raw text. Cute-dbt preserves them\n    # verbatim in the Authoring YAML drawer (cute-dbt#73).\n    given:\n      - input: ref('stg_synthea__payers')\n        format: dict\n        rows:\n          - payer_id: 'a00000aa-0000-0000-0000-000000000001'\n            payer_name: 'Acme Health'\n            address: '1 Acme Way'\n            city: 'Boston'\n            state: 'MA'\n            zip_code: '02101'\n            phone: '555-0100'\n            amount_covered: 1000.0\n            amount_uncovered: 250.0\n            revenue: 1250.0\n            covered_encounters: 10\n            uncovered_encounters: 2\n            covered_medications: 5\n            uncovered_medications: 1\n            covered_procedures: 3\n            uncovered_procedures: 0\n            covered_immunizations: 4\n            uncovered_immunizations: 0\n            unique_customers: 8\n            average_quality_of_life_score: 0.85\n            member_months: 96\n    expect:\n      format: dict\n      rows:\n        - payer_key: -1\n          payer_id: 'UNKNOWN'\n          payer_name: 'Unknown Payer'\n        - payer_key: 1\n          payer_id: 'a00000aa-0000-0000-0000-000000000001'\n          payer_name: 'Acme Health'\n  # The TRAILING bracket — contiguous `#`-comment lines at the SAME\n  # indent as `- name:`, immediately following the test body and\n  # terminated by EOF or a blank line, are attached to this test's\n  # slice. Useful for cross-references and follow-up notes (cute-dbt#73).","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"}],"suppressed":{"source":"pragma","reason":"unknown_member is a constant sentinel arm, exercised by design"},"pin_node":"final"}]},{"name":"fct_clinical_events","path":"models/marts/core/fct_clinical_events.sql","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_encounters_incremental","path":"models/marts/core/fct_encounters_incremental.sql","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":true,"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","authoring_yaml":"  # cute-dbt#145 — an incremental-model unit test. `overrides.macros.\n  # is_incremental: true` drives the model's is_incremental() branch,\n  # `given: - input: this` supplies the model's prior state, and Expected is\n  # the rows MERGED/INSERTED by the run — not the final table after the merge.\n  - name: test_fct_encounters_incremental_appends_new_encounters\n    description: |\n      fct_encounters_incremental appends encounters newer than the latest\n      already-loaded start_time. With is_incremental() true, only the new\n      encounter (e2) is merged; the prior row (e1, supplied via `this`) is\n      untouched, so Expected is the single inserted row — the materialization\n      delta, not the resulting table.\n    model: fct_encounters_incremental\n    overrides:\n      macros:\n        is_incremental: true\n    given:\n      - input: this\n        format: dict\n        rows:\n          - encounter_id: 'e1'\n            patient_id: 'p1'\n            encounter_type: 'wellness'\n            start_time: '2025-01-01 09:00:00'\n            total_cost: 100.0\n      - input: ref('stg_synthea__encounters')\n        format: dict\n        rows:\n          - encounter_id: 'e1'\n            patient_id: 'p1'\n            encounter_type: 'wellness'\n            start_time: '2025-01-01 09:00:00'\n            total_cost: 100.0\n          - encounter_id: 'e2'\n            patient_id: 'p2'\n            encounter_type: 'emergency'\n            start_time: '2025-02-01 14:30:00'\n            total_cost: 500.0\n    expect:\n      format: dict\n      rows:\n        - encounter_id: 'e2'\n          patient_id: 'p2'\n          encounter_type: 'emergency'\n          start_time: '2025-02-01 14:30:00'\n          total_cost: 500.0","is_incremental_mode":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)"}]},{"name":"int_dq_quarantine__encounters","path":"models/intermediate/quarantine/int_dq_quarantine__encounters.sql","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":"mart_date_state_grid","path":"models/marts/analytics/mart_date_state_grid.sql","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","authoring_yaml":"  # Cross-join demo (cute-dbt#64): mart_date_state_grid's CROSS JOIN\n  # CTE gives cute-dbt's renderer a real cross-join edge to draw. This\n  # test also mixes given formats (dict + csv) in a single unit_test.\n  - name: test_mart_date_state_grid_cross_joins_months_and_states\n    description: |\n      mart_date_state_grid CROSS JOINs the distinct calendar months from\n      dim_date with the distinct non-null patient states from staging.\n      Three daily dim_date rows collapse to two months; four patient\n      rows collapse to two states (one NULL filtered out, one duplicate\n      deduplicated). The result is the full 2 x 2 cartesian product —\n      four grid rows. Mixes a dict given (dim_date) with a csv given\n      (patients) in one test.\n    model: mart_date_state_grid\n    given:\n      - input: ref('dim_date')\n        format: dict\n        rows:\n          - date_actual: 2024-01-15\n            year_actual: 2024\n            month_actual: 1\n            month_name: 'January'\n          - date_actual: 2024-01-16\n            year_actual: 2024\n            month_actual: 1\n            month_name: 'January'\n          - date_actual: 2024-02-01\n            year_actual: 2024\n            month_actual: 2\n            month_name: 'February'\n      - input: ref('stg_synthea__patients')\n        format: csv\n        rows: |\n          patient_id,state\n          a00000aa-0000-0000-0000-000000000001,Massachusetts\n          a00000aa-0000-0000-0000-000000000002,Connecticut\n          a00000aa-0000-0000-0000-000000000003,\n          a00000aa-0000-0000-0000-000000000004,Massachusetts\n    expect:\n      format: csv\n      rows: |\n        month_key,year_actual,month_actual,month_name,state\n        202401,2024,1,January,Massachusetts\n        202401,2024,1,January,Connecticut\n        202402,2024,2,February,Massachusetts\n        202402,2024,2,February,Connecticut","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","table":{"columns":["patient_id","state"],"rows":[{"cells":[{"display":"a00000aa-0000-0000-0000-000000000001","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000001"}},{"display":"Massachusetts","key":{"t":"str","v":"Massachusetts"}}]},{"cells":[{"display":"a00000aa-0000-0000-0000-000000000002","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000002"}},{"display":"Connecticut","key":{"t":"str","v":"Connecticut"}}]},{"cells":[{"display":"a00000aa-0000-0000-0000-000000000003","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000003"}},{"display":"","key":{"t":"null"}}]},{"cells":[{"display":"a00000aa-0000-0000-0000-000000000004","key":{"t":"str","v":"a00000aa-0000-0000-0000-000000000004"}},{"display":"Massachusetts","key":{"t":"str","v":"Massachusetts"}}]}]},"rows":[{"patient_id":"a00000aa-0000-0000-0000-000000000001","state":"Massachusetts"},{"patient_id":"a00000aa-0000-0000-0000-000000000002","state":"Connecticut"},{"patient_id":"a00000aa-0000-0000-0000-000000000003","state":null},{"patient_id":"a00000aa-0000-0000-0000-000000000004","state":"Massachusetts"}],"format":"csv","column_meta":{"patient_id":{"description":"Unique patient identifier (UUID)","tests":[{"name":"not null"},{"name":"unique"}]},"state":{"description":"State of residence (full state name, e.g., Massachusetts)"}}}],"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","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","authoring_yaml":"  # LEADING bracket for test 1 — the slicer attaches contiguous\n  # `#`-comment lines at the SAME indent as `- name:` immediately above\n  # the test (no blank-line gap below) to this test's authored slice\n  # (cute-dbt#69 / #73).\n  - name: test_mart_dq_summary_combines_encounter_and_medication_metrics\n    description: |\n      mart_dq_summary UNION-ALLs metrics from stg_synthea__encounters\n      and stg_synthea__medications. This test mocks two encounter rows\n      (one invalid) and two medication rows (both invalid), then asserts\n      the per-entity counts + quarantine rate. Uses csv format for both\n      GIVEN and EXPECT — compact tabular form across many boolean\n      dq-flag columns.\n    model: mart_dq_summary\n    # INSIDE bracket for test 1 — comments at deeper indent than\n    # `- name:` ride along with the body slice as raw text (cute-dbt#69\n    # / #73).\n    given:\n      - input: ref('stg_synthea__encounters')\n        format: csv\n        rows: |\n          is_dq_valid,valid_encounter_timestamps,no_future_encounter_dates,end_after_1900,start_after_1900\n          false,false,true,true,true\n          true,true,true,true,true\n      - input: ref('stg_synthea__medications')\n        format: csv\n        rows: |\n          is_dq_valid,valid_medication_dates,no_future_medication_dates,start_after_1900,end_after_1900_if_present\n          false,false,true,true,true\n          false,true,false,true,true\n    expect:\n      format: csv\n      rows: |\n        entity_type,quarantined_count,total_count,quarantine_rate_pct,failed_timestamp_validations\n        encounters,1,2,50.00,1\n        medications,2,2,100.00,1\n  # TRAILING bracket for test 1 — the comment block butts against the\n  # body above (no blank-line gap) and is terminated below by the blank\n  # line separating the two tests (cute-dbt#69 / #73).","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","authoring_yaml":"  # LEADING bracket for test 2 — sits between the blank-line\n  # terminator above and `- name:` below with no further gap, so the\n  # leading-wins tiebreaker is moot here (cute-dbt#69 / #73).\n  - name: test_mart_dq_summary_zero_quarantined_when_all_valid\n    description: |\n      mart_dq_summary should report zero quarantined_count and 0.00\n      quarantine_rate_pct when every upstream row passes data-quality\n      validations. Uses sql format for the GIVEN mocks and dict format\n      for the EXPECT — dict expects only compare listed columns, so\n      non-deterministic outputs (`_generated_at` from\n      `current_timestamp`) are excluded from comparison.\n    model: mart_dq_summary\n    # INSIDE bracket for test 2 — same rule as test 1 (cute-dbt#69 /\n    # #73). Demonstrates that the slicer ride-along applies to every\n    # unit_test, not just the first in the file.\n    given:\n      - input: ref('stg_synthea__encounters')\n        format: sql\n        rows: |\n          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\n      - input: ref('stg_synthea__medications')\n        format: sql\n        rows: |\n          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\n    expect:\n      format: dict\n      rows:\n        - entity_type: 'encounters'\n          quarantined_count: 0\n          total_count: 1\n          quarantine_rate_pct: 0.00\n        - entity_type: 'medications'\n          quarantined_count: 0\n          total_count: 1\n          quarantine_rate_pct: 0.00\n    overrides:\n      macros:\n        dbt.current_timestamp: \"'2024-01-15 00:00:00'\"\n      vars:\n        dq_quarantine_threshold: 5\n      env_vars:\n        DBT_DQ_REGION: 'us-east-1'\n  # TRAILING bracket for test 2 — terminated by the blank line\n  # separating it from test 3 (cute-dbt#69 / #73).","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__patients","path":"models/staging/synthea/stg_synthea__patients.sql","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","authoring_yaml":"  - name: test_stg_synthea__patients_renames_and_hashes_source_columns\n    description: |\n      stg_synthea__patients renames the raw Synthea UPPERCASE columns to\n      snake_case and hashes the SSN with md5. The given mocks the\n      synthea_raw.patients SOURCE directly (inline dict rows) — the only\n      unit test in this project whose input is a source() rather than a\n      ref() (cute-dbt#57). Dict expect compares listed columns only, so\n      the non-deterministic _loaded_at (current_timestamp) is excluded\n      from assertion automatically.\n    model: stg_synthea__patients\n    given:\n      - input: source('synthea_raw', 'patients')\n        format: dict\n        rows:\n          - Id: 'c0000000-0000-0000-0000-000000000001'\n            FIRST: 'Ada'\n            LAST: 'Lovelace'\n            GENDER: 'F'\n            CITY: 'Boston'\n            STATE: 'Massachusetts'\n            SSN: '999-99-9999'\n    expect:\n      format: dict\n      rows:\n        - patient_id: 'c0000000-0000-0000-0000-000000000001'\n          first_name: 'Ada'\n          last_name: 'Lovelace'\n          gender: 'F'\n          city: 'Boston'\n          state: 'Massachusetts'\n          ssn_hash: '257cf696294931925796925d89aa0afb'","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}],"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"},"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>
 /*! jQuery v3.7.1 | (c) OpenJS Foundation and other contributors | jquery.org/license */
diff --git a/src/adapters/manifest.rs b/src/adapters/manifest.rs
index a402efa3..f0ab7fe5 100644
--- a/src/adapters/manifest.rs
+++ b/src/adapters/manifest.rs
@@ -44,7 +44,7 @@ use serde::Deserialize;
 
 use crate::domain::{
     Checksum, DependsOn, Manifest, ManifestMetadata, Node, NodeConfig, NodeId, PreflightError,
-    TestMetadata, UnitTest, UnitTestExpect, UnitTestGiven,
+    SourceNode, TestMetadata, UnitTest, UnitTestExpect, UnitTestGiven,
 };
 use crate::ports::ManifestSource;
 use serde_json::Value;
@@ -78,6 +78,8 @@ struct WireManifest {
     unit_tests: HashMap<String, WireUnitTest>,
     #[serde(default)]
     macros: HashMap<String, WireMacro>,
+    #[serde(default)]
+    sources: HashMap<String, WireSource>,
 }
 
 /// Wire projection of one `nodes` entry.
@@ -184,6 +186,53 @@ struct WireMacro {
     macro_sql: String,
 }
 
+/// Wire projection of one top-level `sources` entry (cute-dbt#57).
+///
+/// Like [`WireNode`], no `id` field — dbt keys the `sources` map by
+/// `unique_id` (`source.<package>.<source_name>.<name>`) and the map key
+/// is folded into the domain [`SourceNode`] during translation.
+///
+/// **Every** field is `#[serde(default)] Option<…>` — the cute-dbt#145
+/// engine-divergence rule applied verbatim: dbt-core emits explicit
+/// `null` for unset fields (an `Option` is required; a bare `String`
+/// rejects `null`), while fusion's `#[skip_serializing_none]` omits the
+/// keys entirely (`default` covers absence). One malformed source entry
+/// must never fail the whole manifest parse (ADR-5); a source whose
+/// `source_name` / `name` defaults to `""` simply never matches a parsed
+/// `source('a', 'b')` given — the same fail-open posture as an
+/// unresolvable `ref(...)`.
+#[derive(Debug, Deserialize)]
+struct WireSource {
+    #[serde(default)]
+    source_name: Option<String>,
+    #[serde(default)]
+    name: Option<String>,
+    #[serde(default)]
+    identifier: Option<String>,
+    #[serde(default)]
+    schema: Option<String>,
+    #[serde(default)]
+    database: Option<String>,
+    #[serde(default)]
+    relation_name: Option<String>,
+}
+
+impl WireSource {
+    /// Translate into the domain [`SourceNode`], folding the
+    /// authoritative map `key` into the id (the [`WireNode`] precedent).
+    fn into_domain(self, key: String) -> SourceNode {
+        SourceNode::new(
+            NodeId::new(key),
+            self.source_name.unwrap_or_default(),
+            self.name.unwrap_or_default(),
+            self.identifier,
+            self.schema.unwrap_or_default(),
+            self.database,
+            self.relation_name,
+        )
+    }
+}
+
 /// Wire projection of one `unit_tests` map entry.
 ///
 /// The domain [`UnitTest`] type stores `tags` and `meta` flat, but the
@@ -360,7 +409,12 @@ impl WireManifest {
             .into_iter()
             .map(|(key, wire)| (key, wire.macro_sql))
             .collect();
-        Manifest::new(self.metadata, nodes, unit_tests, macros)
+        let sources = self
+            .sources
+            .into_iter()
+            .map(|(key, wire)| (NodeId::new(key.clone()), wire.into_domain(key)))
+            .collect();
+        Manifest::new(self.metadata, nodes, unit_tests, macros).with_sources(sources)
     }
 }
 
@@ -783,6 +837,91 @@ mod tests {
         assert!(manifest.nodes().is_empty());
         assert!(manifest.unit_tests().is_empty());
         assert!(manifest.macros().is_empty());
+        assert!(manifest.sources().is_empty());
+    }
+
+    // ----- cute-dbt#57: top-level `sources` block ---------------------
+
+    #[test]
+    fn parse_manifest_translates_a_core_style_source_entry() {
+        // dbt-core 1.11 dialect: unset Option fields serialize as
+        // explicit `null` (here `database`), and the entry carries
+        // sibling keys cute-dbt does not consume (ADR-5 tolerance).
+        let json = format!(
+            r#"{{
+              "metadata": {{ "dbt_schema_version": "{V12_URL}" }},
+              "sources": {{
+                "source.shop.synthea_raw.patients": {{
+                  "database": null,
+                  "schema": "main",
+                  "name": "patients",
+                  "resource_type": "source",
+                  "source_name": "synthea_raw",
+                  "identifier": "patients",
+                  "relation_name": "\"memory\".\"main\".\"patients\"",
+                  "loaded_at_field": null,
+                  "freshness": null,
+                  "quoting": {{ "database": null }}
+                }}
+              }}
+            }}"#
+        );
+        let manifest = parse_manifest(&json).expect("core-style source entry parses");
+        assert_eq!(manifest.sources().len(), 1);
+        let source = manifest
+            .source_by_name("synthea_raw", "patients")
+            .expect("the (source_name, name) pair resolves");
+        assert_eq!(source.id().as_str(), "source.shop.synthea_raw.patients");
+        assert_eq!(source.schema(), "main");
+        assert_eq!(source.identifier(), Some("patients"));
+        assert_eq!(source.database(), None, "explicit null → None");
+        assert_eq!(
+            source.relation_name(),
+            Some("\"memory\".\"main\".\"patients\"")
+        );
+    }
+
+    #[test]
+    fn parse_manifest_translates_a_fusion_style_source_entry() {
+        // dbt-fusion dialect: `#[skip_serializing_none]` OMITS unset keys
+        // entirely (no `identifier`, `database`, `relation_name`) — the
+        // cute-dbt#145 absent-key half of the engine-divergence rule.
+        let json = format!(
+            r#"{{
+              "metadata": {{ "dbt_schema_version": "{V12_URL}" }},
+              "sources": {{
+                "source.shop.synthea_raw.encounters": {{
+                  "schema": "main",
+                  "name": "encounters",
+                  "source_name": "synthea_raw"
+                }}
+              }}
+            }}"#
+        );
+        let manifest = parse_manifest(&json).expect("fusion-style source entry parses");
+        let source = manifest
+            .source_by_name("synthea_raw", "encounters")
+            .expect("the (source_name, name) pair resolves");
+        assert_eq!(source.identifier(), None);
+        assert_eq!(source.database(), None);
+        assert_eq!(source.relation_name(), None);
+    }
+
+    #[test]
+    fn parse_manifest_tolerates_a_degenerate_source_entry() {
+        // A sources entry with every consumed key absent must not fail
+        // the whole manifest (ADR-5); it translates to empty-string
+        // names that can never match a parsed `source('a','b')` given —
+        // the fail-open posture of an unresolvable ref.
+        let json = format!(
+            r#"{{
+              "metadata": {{ "dbt_schema_version": "{V12_URL}" }},
+              "sources": {{ "source.shop.broken.entry": {{}} }}
+            }}"#
+        );
+        let manifest = parse_manifest(&json).expect("degenerate source entry tolerated");
+        assert_eq!(manifest.sources().len(), 1);
+        assert!(manifest.source_by_name("broken", "entry").is_none());
     }
 
     // ----- cute-dbt#165: column descriptions + test attribution ------
diff --git a/src/adapters/render.rs b/src/adapters/render.rs
index c26d7c9f..d4ca108d 100644
--- a/src/adapters/render.rs
+++ b/src/adapters/render.rs
@@ -68,9 +68,9 @@ use crate::adapters::asset_embed::{
 use crate::adapters::cte_engine::{TERMINAL_NODE_NAME, parse_cte_graph};
 use crate::domain::{
     BANNER_EMPTY_SCOPE, BlockDiff, CheckId, CheckPolicy, CteGraph, EdgeType, Finding, FixtureTable,
-    HeuristicId, InScopeSet, Instrument, Manifest, ModelInScopeSet, Node, NodeId, TestMetadata,
-    Tier, UnitTest, UnitTestDataDiff, UnitTestGiven, UnitTestYamlBlock, apply_check_policy,
-    model_findings, resolve_target_model, table_from_manifest_rows,
+    HeuristicId, InScopeSet, Instrument, Manifest, ModelInScopeSet, Node, NodeId, SourceNode,
+    TestMetadata, Tier, UnitTest, UnitTestDataDiff, UnitTestGiven, UnitTestYamlBlock,
+    apply_check_policy, model_findings, resolve_target_model, table_from_manifest_rows,
 };
 
 /// Snake-case wire key for an [`EdgeType`] — the exact JSON-serde string
@@ -142,6 +142,48 @@ pub fn parse_ref_name(input: &str) -> Option<&str> {
     if name.is_empty() { None } else { Some(name) }
 }
 
+/// Parse the `(source_name, table_name)` pair out of a unit-test
+/// `given[].input` string of the form `source('a', 'b')` (cute-dbt#57)
+/// — the exact sibling of [`parse_ref_name`].
+///
+/// Both engines serialize the given input **verbatim** from the authored
+/// YAML (fusion clones the string into the manifest node; core
+/// round-trips it byte-for-byte), and dbt's `source()` Jinja function
+/// takes exactly two arguments, so the manifest string is the literal
+/// authored call. The same tolerances as [`parse_ref_name`] apply:
+/// case-insensitive keyword (`source` / `SOURCE` / …), whitespace
+/// between the keyword and the parenthesis and around the arguments,
+/// single quotes only (dbt's documented/dominant serialized form —
+/// double-quoted and `name=`/`table_name=` kwargs variants are
+/// engine-valid but rare and deliberately deferred, exactly as the ref
+/// parser defers them).
+///
+/// Returns `None` when the input does not match the `source('…','…')`
+/// shape or when either name is empty. The caller treats `None` as "no
+/// import-CTE match" and surfaces the design's empty-state copy
+/// (fail-open, same as an unresolvable `ref`).
+#[must_use]
+pub fn parse_source_ref(input: &str) -> Option<(&str, &str)> {
+    let trimmed = input.trim();
+    let prefix = trimmed.get(..6)?;
+    if !prefix.eq_ignore_ascii_case("source") {
+        return None;
+    }
+    let after_keyword = trimmed[6..].trim_start();
+    let inside = after_keyword.strip_prefix('(')?.strip_suffix(')')?;
+    // Top-level comma split: a comma inside a quoted name would leave
+    // the first fragment with unbalanced quotes, fail the quote strip
+    // below, and fall through to `None` — fail-open by construction.
+    let (first, second) = inside.split_once(',')?;
+    let source_name = first.trim().strip_prefix('\'')?.strip_suffix('\'')?;
+    let table_name = second.trim().strip_prefix('\'')?.strip_suffix('\'')?;
+    if source_name.is_empty() || table_name.is_empty() {
+        None
+    } else {
+        Some((source_name, table_name))
+    }
+}
+
 /// Bind a unit test's `given[]` entries to a named import-CTE.
 ///
 /// Returns the first `given` whose `input` parses to `ref('NAME')` with
@@ -1491,8 +1533,19 @@ fn build_test_payload(
         .iter()
         .enumerate()
         .map(|(ordinal, g)| {
-            let bound_to_node =
-                parse_ref_name(g.input()).and_then(|ref_name| find_import_node_id(graph, ref_name));
+            // Bind the given to a leaf CTE: `ref(...)` matches directly
+            // by model name; `source(...)` resolves through the
+            // manifest's sources map first (cute-dbt#57) because dbt
+            // pre-resolves source refs at compile time. The two arms are
+            // disjoint by construction (an input parses as at most one
+            // shape), so `or_else` is chain order, not precedence.
+            let bound_to_node = parse_ref_name(g.input())
+                .and_then(|ref_name| find_import_node_id(graph, ref_name))
+                .or_else(|| {
+                    parse_source_ref(g.input()).and_then(|(source_name, table_name)| {
+                        find_source_import_node_id(current, graph, source_name, table_name)
+                    })
+                });
             let loaded = external.and_then(|e| e.given.get(&ordinal));
             let (rows, table, format) =
                 resolve_fixture_payload(g.rows(), g.format(), g.fixture(), loaded);
@@ -1647,6 +1700,87 @@ fn find_import_node_id(graph: &CteGraph, ref_name: &str) -> Option<String> {
     None
 }
 
+/// Locate the leaf CTE node that binds to a `source('a', 'b')` given
+/// (cute-dbt#57) — the source-side sibling of [`find_import_node_id`].
+///
+/// dbt compiles `{{ source('a', 'b') }}` into the resolved relation at
+/// `dbt compile` time, so the compiled SQL the CTE engine sees never
+/// carries the literal `source(...)` form — only the resolved relation
+/// (`"db"."schema"."table"`). Binding therefore walks the manifest's
+/// `sources` map:
+///
+/// 1. Resolve `(source_name, table_name)` — the two authored `source()`
+///    arguments — against [`Manifest::source_by_name`]. The lookup is on
+///    `source_name` + `name`, **not** `identifier` (the args are the
+///    YAML names; `identifier` may be overridden to differ).
+/// 2. Derive the match token from the hit: the physical `identifier`
+///    (quote-stripped — dbt preserves embedded quote characters
+///    verbatim, the reserved-word `"GROUP"` case), falling back to the
+///    last dot-segment of `relation_name`, falling back to `name`
+///    (dbt's own identifier default).
+/// 3. Feed the token through the existing two-pass
+///    [`find_import_node_id`]: the CTE engine already reduces every
+///    FROM/JOIN leaf to the lowercased, quote-stripped **last
+///    identifier** of the relation, and the compiled-SQL relation text
+///    and the manifest `relation_name` render from the same relation
+///    object in both engines — so the leaf token match is exactly the
+///    normalization the ref path already uses. No FQN machinery.
+///
+/// Returns `None` when the pair is missing from the sources map or no
+/// leaf CTE references the relation — the same fail-open empty-state as
+/// an unresolvable `ref` (sources need no preflight: they are referenced
+/// by models, never analyzed themselves).
+fn find_source_import_node_id(
+    manifest: &Manifest,
+    graph: &CteGraph,
+    source_name: &str,
+    table_name: &str,
+) -> Option<String> {
+    let source = manifest.source_by_name(source_name, table_name)?;
+    let token = source_relation_token(source);
+    if token.is_empty() {
+        return None;
+    }
+    find_import_node_id(graph, token)
+}
+
+/// The leaf table identifier a resolved [`SourceNode`] is expected to
+/// appear as inside a compiled CTE body: `identifier` when present and
+/// non-empty (quote-stripped), else the last dot-segment of
+/// `relation_name` (quote-stripped; naive split — a dot embedded in a
+/// quoted identifier is out of scope, the identifier-first chain makes
+/// this fallback rare), else the source's `name`. Returns a borrowed
+/// slice of the [`SourceNode`]'s own fields — every branch is a
+/// quote-strip view, so no allocation is needed (Gemini PR 204).
+fn source_relation_token(source: &SourceNode) -> &str {
+    let identifier = source
+        .identifier()
+        .map(strip_ident_quotes)
+        .filter(|ident| !ident.is_empty());
+    let from_relation = || {
+        source
+            .relation_name()
+            .and_then(|relation| relation.rsplit('.').next())
+            .map(strip_ident_quotes)
+            .filter(|segment| !segment.is_empty())
+    };
+    identifier
+        .or_else(from_relation)
+        .unwrap_or_else(|| strip_ident_quotes(source.name()))
+}
+
+/// Strip the common SQL identifier quoting characters from both ends of
+/// `s`: double quotes (ANSI / dbt `relation_name`), backticks (`BigQuery`
+/// / `MySQL`), and square brackets (T-SQL). Interior characters are kept
+/// verbatim; lowercasing is the caller's concern
+/// ([`find_import_node_id`] case-folds both sides).
+fn strip_ident_quotes(s: &str) -> &str {
+    s.trim()
+        .trim_matches(|c| c == '"' || c == '`')
+        .trim_start_matches('[')
+        .trim_end_matches(']')
+}
+
 /// `true` when the node at `index` is a candidate for pass-2 binding —
 /// i.e. a leaf CTE that may carry engine-extracted body-leaf refs.
 ///
@@ -1780,6 +1914,135 @@ mod tests {
         assert_eq!(parse_ref_name("plain_table"), None);
     }
 
+    // ===== parse_source_ref (cute-dbt#57) =====
+
+    #[test]
+    fn parse_source_ref_extracts_both_single_quoted_names() {
+        assert_eq!(
+            parse_source_ref("source('synthea_raw', 'patients')"),
+            Some(("synthea_raw", "patients")),
+        );
+    }
+
+    #[test]
+    fn parse_source_ref_tolerates_whitespace_variants() {
+        // Surrounding, keyword↔paren, and around-the-comma whitespace —
+        // mirrors parse_ref_name's Jinja-tolerance.
+        assert_eq!(parse_source_ref("  source('a', 'b')  "), Some(("a", "b")));
+        assert_eq!(parse_source_ref("source ('a','b')"), Some(("a", "b")));
+        assert_eq!(parse_source_ref("SOURCE\t('a' , 'b')"), Some(("a", "b")));
+        assert_eq!(parse_source_ref("source( 'a','b' )"), Some(("a", "b")));
+    }
+
+    #[test]
+    fn parse_source_ref_accepts_case_variant_keyword() {
+        assert_eq!(parse_source_ref("SOURCE('A', 'B')"), Some(("A", "B")));
+        assert_eq!(parse_source_ref("Source('a', 'b')"), Some(("a", "b")));
+        assert_eq!(parse_source_ref("sOuRcE('a', 'b')"), Some(("a", "b")));
+    }
+
+    #[test]
+    fn parse_source_ref_returns_none_on_missing_parens_or_arg() {
+        assert_eq!(parse_source_ref("source'a','b'"), None);
+        assert_eq!(
+            parse_source_ref("source('a')"),
+            None,
+            "one arg is not a source ref"
+        );
+        assert_eq!(parse_source_ref("source('a', 'b'"), None);
+    }
+
+    #[test]
+    fn parse_source_ref_returns_none_on_empty_names() {
+        assert_eq!(parse_source_ref("source('', 'b')"), None);
+        assert_eq!(parse_source_ref("source('a', '')"), None);
+        assert_eq!(parse_source_ref("source('', '')"), None);
+    }
+
+    #[test]
+    fn parse_source_ref_returns_none_on_double_quoted_names() {
+        // Same deliberate strictness as parse_ref_name: dbt manifests
+        // serialize the dominant single-quoted authored form.
+        assert_eq!(parse_source_ref("source(\"a\", \"b\")"), None);
+    }
+
+    #[test]
+    fn parse_source_ref_returns_none_on_unmatched_quotes() {
+        assert_eq!(parse_source_ref("source('a, 'b')"), None);
+        assert_eq!(parse_source_ref("source('a', b')"), None);
+    }
+
+    #[test]
+    fn parse_source_ref_returns_none_on_non_source_input() {
+        assert_eq!(parse_source_ref("ref('stg_orders')"), None);
+        assert_eq!(parse_source_ref("this"), None);
+        assert_eq!(parse_source_ref(""), None);
+        assert_eq!(parse_source_ref("plain_table"), None);
+    }
+
+    // ===== source_relation_token / strip_ident_quotes (cute-dbt#57) =====
+
+    fn source_node(
+        identifier: Option<&str>,
+        relation_name: Option<&str>,
+        name: &str,
+    ) -> SourceNode {
+        SourceNode::new(
+            NodeId::new(format!("source.shop.raw.{name}")),
+            "raw",
+            name,
+            identifier.map(str::to_owned),
+            "main",
+            Some("memory".to_owned()),
+            relation_name.map(str::to_owned),
+        )
+    }
+
+    #[test]
+    fn source_relation_token_prefers_the_identifier() {
+        let s = source_node(
+            Some("patients_v2"),
+            Some("\"memory\".\"main\".\"patients_v2\""),
+            "patients",
+        );
+        assert_eq!(source_relation_token(&s), "patients_v2");
+    }
+
+    #[test]
+    fn source_relation_token_strips_embedded_identifier_quotes() {
+        // dbt preserves a reserved-word identifier verbatim INCLUDING
+        // its quote characters (the zendesk `"GROUP"` case).
+        let s = source_node(Some("\"GROUP\""), None, "group");
+        assert_eq!(source_relation_token(&s), "GROUP");
+    }
+
+    #[test]
+    fn source_relation_token_falls_back_to_relation_name_last_segment() {
+        let s = source_node(
+            None,
+            Some("\"memory\".\"main\".\"patients\""),
+            "patients_yaml",
+        );
+        assert_eq!(source_relation_token(&s), "patients");
+    }
+
+    #[test]
+    fn source_relation_token_falls_back_to_the_source_name_field() {
+        // The fusion-minimal entry: no identifier, no relation_name —
+        // dbt defaults the physical identifier to `name`.
+        let s = source_node(None, None, "patients");
+        assert_eq!(source_relation_token(&s), "patients");
+    }
+
+    #[test]
+    fn strip_ident_quotes_handles_each_quoting_dialect() {
+        assert_eq!(strip_ident_quotes("\"orders\""), "orders");
+        assert_eq!(strip_ident_quotes("`orders`"), "orders");
+        assert_eq!(strip_ident_quotes("[orders]"), "orders");
+        assert_eq!(strip_ident_quotes("  orders  "), "orders");
+        assert_eq!(strip_ident_quotes("orders"), "orders");
+    }
+
     // ===== bind_import_to_given =====
 
     fn sample_given(input: &str) -> UnitTestGiven {
@@ -2033,6 +2296,15 @@ mod tests {
         )
     }
 
+    fn manifest_with_sources(
+        nodes: Vec<Node>,
+        tests: Vec<(&str, UnitTest)>,
+        sources: Vec<SourceNode>,
+    ) -> Manifest {
+        manifest_for(nodes, tests)
+            .with_sources(sources.into_iter().map(|s| (s.id().clone(), s)).collect())
+    }
+
     #[test]
     fn build_payload_threads_baseline_label_through() {
         let manifest = manifest_for(vec![], vec![]);
@@ -3218,6 +3490,235 @@ mod tests {
         assert!(test.given[0].bound_to_node.is_none());
     }
 
+    // ===== source() given binding (cute-dbt#57) =====
+
+    /// The canonical staging-model shape: `with source as (select * from
+    /// {{ source('synthea_raw', 'patients') }})` compiles to a quoted
+    /// three-part relation inside an import CTE named `source`.
+    fn patients_source_model() -> Node {
+        let compiled = "with source as (\
+                          select * from \"memory\".\"main\".\"patients\"\
+                        ) select id, name from source";
+        model_node("model.shop.stg_patients", "body", Some(compiled))
+    }
+
+    fn source_given_unit_test(input: &str) -> UnitTest {
+        UnitTest::new(
+            "test_one",
+            NodeId::new("stg_patients"),
+            vec![UnitTestGiven::new(input, json!([]), None, None)],
+            UnitTestExpect::new(json!([]), None, None),
+            None,
+            DependsOn::default(),
+            None,
+            None,
+            None,
+        )
+    }
+
+    fn bound_node_for(manifest: &Manifest) -> Option<String> {
+        let in_scope = InScopeSet::from_iter(["unit_test.shop.test_one".to_owned()]);
+        let models = ModelInScopeSet::from_iter([NodeId::new("model.shop.stg_patients")]);
+        let payload = build_payload(
+            manifest,
+            &in_scope,
+            &models,
+            &HashMap::new(),
+            &HashMap::new(),
+            &HashMap::new(),
+            &HashMap::new(),
+            "b",
+        );
+        payload.models[0].tests[0].given[0].bound_to_node.clone()
+    }
+
+    #[test]
+    fn build_payload_source_given_binds_via_resolved_relation_body_match() {
+        // The cute-dbt#57 vertical: `source('synthea_raw','patients')`
+        // resolves through the manifest sources map to the physical
+        // identifier `patients`, which pass-2 finds in the `source`
+        // CTE's body-leaf refs (the compiled relation and the manifest
+        // relation_name render from the same relation object).
+        let manifest = manifest_with_sources(
+            vec![patients_source_model()],
+            vec![(
+                "unit_test.shop.test_one",
+                source_given_unit_test("source('synthea_raw', 'patients')"),
+            )],
+            vec![SourceNode::new(
+                NodeId::new("source.shop.synthea_raw.patients"),
+                "synthea_raw",
+                "patients",
+                Some("patients".to_owned()),
+                "main",
+                Some("memory".to_owned()),
+                Some("\"memory\".\"main\".\"patients\"".to_owned()),
+            )],
+        );
+        assert_eq!(
+            bound_node_for(&manifest).as_deref(),
+            Some("source"),
+            "source('synthea_raw','patients') binds to the import CTE via the resolved relation",
+        );
+    }
+
+    #[test]
+    fn build_payload_source_given_binds_through_an_identifier_override() {
+        // The YAML `name` and the physical `identifier` differ — the
+        // lookup must run on (source_name, name) while the body match
+        // must run on `identifier`.
+        let compiled = "with src as (\
+                          select * from \"memory\".\"main\".\"patients_v2\"\
+                        ) select id from src";
+        let node = model_node("model.shop.stg_patients", "body", Some(compiled));
+        let manifest = manifest_with_sources(
+            vec![node],
+            vec![(
+                "unit_test.shop.test_one",
+                source_given_unit_test("source('synthea_raw', 'patients')"),
+            )],
+            vec![SourceNode::new(
+                NodeId::new("source.shop.synthea_raw.patients"),
+                "synthea_raw",
+                "patients",
+                Some("patients_v2".to_owned()),
+                "main",
+                Some("memory".to_owned()),
+                Some("\"memory\".\"main\".\"patients_v2\"".to_owned()),
+            )],
+        );
+        assert_eq!(bound_node_for(&manifest).as_deref(), Some("src"));
+    }
+
+    #[test]
+    fn build_payload_source_given_binds_with_a_fusion_minimal_source_entry() {
+        // Fusion-style entry: identifier and relation_name keys absent.
+        // The token falls back to the source's `name` (dbt's identifier
+        // default), which still matches the compiled body leaf.
+        let manifest = manifest_with_sources(
+            vec![patients_source_model()],
+            vec![(
+                "unit_test.shop.test_one",
+                source_given_unit_test("source('synthea_raw', 'patients')"),
+            )],
+            vec![SourceNode::new(
+                NodeId::new("source.shop.synthea_raw.patients"),
+                "synthea_raw",
+                "patients",
+                None,
+                "main",
+                None,
+                None,
+            )],
+        );
+        assert_eq!(bound_node_for(&manifest).as_deref(), Some("source"));
+    }
+
+    #[test]
+    fn build_payload_source_given_does_not_bind_when_pair_is_unresolvable() {
+        // No matching (source_name, name) in the sources map — the given
+        // stays unbound and the node-detail panel keeps its empty-state
+        // copy (fail-open, no PreflightError; sources need no preflight).
+        let manifest = manifest_with_sources(
+            vec![patients_source_model()],
+            vec![(
+                "unit_test.shop.test_one",
+                source_given_unit_test("source('other_block', 'patients')"),
+            )],
+            vec![SourceNode::new(
+                NodeId::new("source.shop.synthea_raw.patients"),
+                "synthea_raw",
+                "patients",
+                Some("patients".to_owned()),
+                "main",
+                Some("memory".to_owned()),
+                Some("\"memory\".\"main\".\"patients\"".to_owned()),
+            )],
+        );
+        assert!(bound_node_for(&manifest).is_none());
+    }
+
+    #[test]
+    fn build_payload_source_given_does_not_bind_without_a_sources_map() {
+        // Pre-#57 shape: the manifest carries no sources block at all.
+        let manifest = manifest_for(
+            vec![patients_source_model()],
+            vec![(
+                "unit_test.shop.test_one",
+                source_given_unit_test("source('synthea_raw', 'patients')"),
+            )],
+        );
+        assert!(bound_node_for(&manifest).is_none());
+    }
+
+    #[test]
+    fn build_payload_binds_a_ref_given_and_a_source_given_in_one_test() {
+        // The cute-dbt#57 AC shape: one model with BOTH a ref()-based
+        // import CTE and a source()-based import CTE; the unit test
+        // mocks both inputs and each given binds to its own CTE node.
+        let compiled = "with orders as (\
+                          select * from \"memory\".\"main\".\"raw_orders\"\
+                        ), patients as (\
+                          select * from \"memory\".\"raw\".\"patients\"\
+                        ) select o.id, p.name from orders o join patients p on p.id = o.pid";
+        let node = model_node("model.shop.mixed_inputs", "body", Some(compiled));
+        let ut = UnitTest::new(
+            "test_one",
+            NodeId::new("mixed_inputs"),
+            vec![
+                UnitTestGiven::new("ref('raw_orders')", json!([{"id": 1}]), None, None),
+                UnitTestGiven::new(
+                    "source('synthea_raw', 'patients')",
+                    json!([{"id": 1, "name": "x"}]),
+                    None,
+                    None,
+                ),
+            ],
+            UnitTestExpect::new(json!([]), None, None),
+            None,
+            DependsOn::default(),
+            None,
+            None,
+            None,
+        );
+        let manifest = manifest_with_sources(
+            vec![node],
+            vec![("unit_test.shop.test_one", ut)],
+            vec![SourceNode::new(
+                NodeId::new("source.shop.synthea_raw.patients"),
+                "synthea_raw",
+                "patients",
+                Some("patients".to_owned()),
+                "raw",
+                Some("memory".to_owned()),
+                Some("\"memory\".\"raw\".\"patients\"".to_owned()),
+            )],
+        );
+        let in_scope = InScopeSet::from_iter(["unit_test.shop.test_one".to_owned()]);
+        let models = ModelInScopeSet::from_iter([NodeId::new("model.shop.mixed_inputs")]);
+        let payload = build_payload(
+            &manifest,
+            &in_scope,
+            &models,
+            &HashMap::new(),
+            &HashMap::new(),
+            &HashMap::new(),
+            &HashMap::new(),
+            "b",
+        );
+        let test = &payload.models[0].tests[0];
+        assert_eq!(
+            test.given[0].bound_to_node.as_deref(),
+            Some("orders"),
+            "the ref() given binds to the ref-based import CTE",
+        );
+        assert_eq!(
+            test.given[1].bound_to_node.as_deref(),
+            Some("patients"),
+            "the source() given binds to the source-based import CTE",
+        );
+    }
+
     #[test]
     fn build_payload_propagates_is_recursive_flag() {
         // A WITH RECURSIVE query: the engine flags the graph; the
diff --git a/src/domain/manifest.rs b/src/domain/manifest.rs
index be8efcca..51017e11 100644
--- a/src/domain/manifest.rs
+++ b/src/domain/manifest.rs
@@ -590,6 +590,114 @@ impl Node {
     }
 }
 
+/// One entry of the manifest's top-level `sources` map — a dbt
+/// `source()` target (cute-dbt#57).
+///
+/// A **separate POD** from [`Node`], not a kind-variant: dbt itself keeps
+/// sources a distinct type end-to-end (fusion's `ManifestSource` /
+/// `DbtSource` and the dedicated top-level `sources` map in the v12
+/// wire, never merged into `nodes`), and source entries carry **no
+/// `checksum` key**, so reusing [`Node`] would force Option-ing a
+/// required field. Mirrors the `StateComparator` precedent the issue
+/// cites: additive widening, never a domain restructure.
+///
+/// Keyed in [`Manifest::sources`] by the wire map key
+/// (`source.<package>.<source_name>.<name>`); the adapter folds that key
+/// into [`Self::id`] (the [`Node`] identity precedent).
+#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
+pub struct SourceNode {
+    id: NodeId,
+    /// `source()`'s **first** argument — the YAML `sources:` block name.
+    source_name: String,
+    /// `source()`'s **second** argument — the table name within the block.
+    name: String,
+    /// Physical table identifier. dbt defaults it to `name`; users may
+    /// override it, and dbt preserves it **verbatim including embedded
+    /// quote characters** (the reserved-word `"GROUP"` case). `None` when
+    /// an engine omits the key (tolerant ingestion, cute-dbt#145 rule).
+    #[serde(default)]
+    identifier: Option<String>,
+    /// Resolved schema name (required by both engines' schemas).
+    schema: String,
+    /// Resolved database. `Option` — dbt-core emits an explicit `null`
+    /// on some adapters; fusion may emit an empty string.
+    #[serde(default)]
+    database: Option<String>,
+    /// dbt's fully-resolved relation (`"db"."schema"."identifier"`).
+    /// `Option` in **both** engines' schemas — parsed defensively even
+    /// though fusion always populates it.
+    #[serde(default)]
+    relation_name: Option<String>,
+}
+
+impl SourceNode {
+    /// Canonical constructor — every field is owned and explicit.
+    #[must_use]
+    pub fn new(
+        id: NodeId,
+        source_name: impl Into<String>,
+        name: impl Into<String>,
+        identifier: Option<String>,
+        schema: impl Into<String>,
+        database: Option<String>,
+        relation_name: Option<String>,
+    ) -> Self {
+        Self {
+            id,
+            source_name: source_name.into(),
+            name: name.into(),
+            identifier,
+            schema: schema.into(),
+            database,
+            relation_name,
+        }
+    }
+
+    /// Source id (`source.<package>.<source_name>.<name>`).
+    #[must_use]
+    pub fn id(&self) -> &NodeId {
+        &self.id
+    }
+
+    /// The YAML `sources:` block name — `source()`'s first argument.
+    #[must_use]
+    pub fn source_name(&self) -> &str {
+        &self.source_name
+    }
+
+    /// The table name within the block — `source()`'s second argument.
+    #[must_use]
+    pub fn name(&self) -> &str {
+        &self.name
+    }
+
+    /// Physical table identifier (verbatim, may carry embedded quotes).
+    /// `None` when the engine omitted the key.
+    #[must_use]
+    pub fn identifier(&self) -> Option<&str> {
+        self.identifier.as_deref()
+    }
+
+    /// Resolved schema name.
+    #[must_use]
+    pub fn schema(&self) -> &str {
+        &self.schema
+    }
+
+    /// Resolved database, when the engine emitted one.
+    #[must_use]
+    pub fn database(&self) -> Option<&str> {
+        self.database.as_deref()
+    }
+
+    /// dbt's fully-resolved relation (`"db"."schema"."identifier"`),
+    /// when the engine emitted one.
+    #[must_use]
+    pub fn relation_name(&self) -> Option<&str> {
+        self.relation_name.as_deref()
+    }
+}
+
 /// `metadata` block — currently consumed only for the
 /// `dbt_schema_version` floor check (ADR-2 Stage-1, PR 4b).
 #[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
@@ -631,10 +739,20 @@ pub struct Manifest {
     unit_tests: HashMap<String, crate::domain::unit_test::UnitTest>,
     #[serde(default)]
     macros: HashMap<String, String>,
+    /// The manifest's top-level `sources` map (cute-dbt#57), keyed by
+    /// the wire map key (`source.<package>.<source_name>.<name>`).
+    /// Defaults to empty so pre-#57 serialized manifests (and synthetic
+    /// test fixtures without sources) still deserialize.
+    #[serde(default)]
+    sources: HashMap<NodeId, SourceNode>,
 }
 
 impl Manifest {
-    /// Canonical constructor — every field is owned.
+    /// Canonical constructor — every field is owned. `sources` starts
+    /// empty; attach a parsed sources map via [`Self::with_sources`]
+    /// (builder rather than a 5th positional param, the
+    /// [`Node::with_column_descriptions`] precedent — keeps the many
+    /// existing test constructors unchanged).
     #[must_use]
     pub fn new(
         metadata: ManifestMetadata,
@@ -647,9 +765,17 @@ impl Manifest {
             nodes,
             unit_tests,
             macros,
+            sources: HashMap::new(),
         }
     }
 
+    /// Attach the manifest's parsed `sources` map (cute-dbt#57).
+    #[must_use]
+    pub fn with_sources(mut self, sources: HashMap<NodeId, SourceNode>) -> Self {
+        self.sources = sources;
+        self
+    }
+
     /// `metadata` block.
     #[must_use]
     pub fn metadata(&self) -> &ManifestMetadata {
@@ -686,6 +812,27 @@ impl Manifest {
     pub fn macros(&self) -> &HashMap<String, String> {
         &self.macros
     }
+
+    /// All sources keyed by id (cute-dbt#57).
+    #[must_use]
+    pub fn sources(&self) -> &HashMap<NodeId, SourceNode> {
+        &self.sources
+    }
+
+    /// Look up a source by its `(source_name, name)` pair — the two
+    /// arguments of a `source('a', 'b')` given input (cute-dbt#57).
+    ///
+    /// Case-insensitive on both halves, keeping the contract symmetric
+    /// with the renderer's `ref(...)` binding (`eq_ignore_ascii_case`
+    /// throughout). Linear scan — manifests carry few sources and the
+    /// lookup runs once per `source(...)` given.
+    #[must_use]
+    pub fn source_by_name(&self, source_name: &str, name: &str) -> Option<&SourceNode> {
+        self.sources.values().find(|source| {
+            source.source_name().eq_ignore_ascii_case(source_name)
+                && source.name().eq_ignore_ascii_case(name)
+        })
+    }
 }
 
 #[cfg(test)]
@@ -1219,5 +1366,119 @@ mod tests {
         assert!(m.nodes().is_empty());
         assert!(m.unit_tests().is_empty());
         assert!(m.macros().is_empty());
+        assert!(m.sources().is_empty());
+    }
+
+    // ===== SourceNode (cute-dbt#57) =====
+
+    fn sample_source(id: &str, source_name: &str, name: &str) -> SourceNode {
+        SourceNode::new(
+            NodeId::new(id),
+            source_name,
+            name,
+            Some(name.to_owned()),
+            "main",
+            Some("memory".to_owned()),
+            Some(format!("\"memory\".\"main\".\"{name}\"")),
+        )
+    }
+
+    #[test]
+    fn source_node_constructor_and_accessors() {
+        let s = sample_source("source.shop.raw.patients", "raw", "patients");
+        assert_eq!(s.id().as_str(), "source.shop.raw.patients");
+        assert_eq!(s.source_name(), "raw");
+        assert_eq!(s.name(), "patients");
+        assert_eq!(s.identifier(), Some("patients"));
+        assert_eq!(s.schema(), "main");
+        assert_eq!(s.database(), Some("memory"));
+        assert_eq!(s.relation_name(), Some("\"memory\".\"main\".\"patients\""));
+    }
+
+    #[test]
+    fn source_node_serde_round_trips() {
+        let s = sample_source("source.shop.raw.patients", "raw", "patients");
+        let json = serde_json::to_string(&s).unwrap();
+        let back: SourceNode = serde_json::from_str(&json).unwrap();
+        assert_eq!(s, back);
+    }
+
+    #[test]
+    fn source_node_optional_fields_round_trip_as_none() {
+        // The fusion-style minimal entry: identifier / database /
+        // relation_name keys absent (tolerant `#[serde(default)]`).
+        let json = r#"{
+            "id": "source.shop.raw.orders",
+            "source_name": "raw",
+            "name": "orders",
+            "schema": "main"
+        }"#;
+        let s: SourceNode = serde_json::from_str(json).unwrap();
+        assert_eq!(s.identifier(), None);
+        assert_eq!(s.database(), None);
+        assert_eq!(s.relation_name(), None);
+        let back: SourceNode = serde_json::from_str(&serde_json::to_string(&s).unwrap()).unwrap();
+        assert_eq!(s, back);
+    }
+
+    #[test]
+    fn manifest_with_sources_round_trips_through_serde() {
+        let source = sample_source("source.shop.raw.patients", "raw", "patients");
+        let mut sources = HashMap::new();
+        sources.insert(source.id().clone(), source);
+        let m = Manifest::new(
+            ManifestMetadata::new("v12"),
+            HashMap::new(),
+            HashMap::new(),
+            HashMap::new(),
+        )
+        .with_sources(sources);
+        let back: Manifest = serde_json::from_str(&serde_json::to_string(&m).unwrap()).unwrap();
+        assert_eq!(m, back);
+        assert_eq!(back.sources().len(), 1);
+    }
+
+    #[test]
+    fn source_by_name_resolves_the_given_pair_case_insensitively() {
+        let source = sample_source(
+            "source.shop.synthea_raw.patients",
+            "synthea_raw",
+            "patients",
+        );
+        let mut sources = HashMap::new();
+        sources.insert(source.id().clone(), source);
+        let m = Manifest::new(
+            ManifestMetadata::new("v12"),
+            HashMap::new(),
+            HashMap::new(),
+            HashMap::new(),
+        )
+        .with_sources(sources);
+        assert!(m.source_by_name("synthea_raw", "patients").is_some());
+        assert!(
+            m.source_by_name("SYNTHEA_RAW", "Patients").is_some(),
+            "lookup is case-insensitive on both halves (symmetric with the ref binding contract)",
+        );
+    }
+
+    #[test]
+    fn source_by_name_requires_both_halves_to_match() {
+        let source = sample_source(
+            "source.shop.synthea_raw.patients",
+            "synthea_raw",
+            "patients",
+        );
+        let mut sources = HashMap::new();
+        sources.insert(source.id().clone(), source);
+        let m = Manifest::new(
+            ManifestMetadata::new("v12"),
+            HashMap::new(),
+            HashMap::new(),
+            HashMap::new(),
+        )
+        .with_sources(sources);
+        assert!(m.source_by_name("synthea_raw", "encounters").is_none());
+        assert!(m.source_by_name("other_block", "patients").is_none());
+        assert!(m.source_by_name("", "").is_none());
     }
 }
diff --git a/src/domain/mod.rs b/src/domain/mod.rs
index 94f9ecbb..f6563cff 100644
--- a/src/domain/mod.rs
+++ b/src/domain/mod.rs
@@ -67,8 +67,8 @@ pub use checks::{
 pub use config::{AnalysisConfig, DEFAULT_REPORT_TITLE, ReportConfig};
 pub use cte::{CteEdge, CteGraph, CteNode, EdgeType, JoinKeyPair, LeftJoinFact, Span};
 pub use manifest::{
-    Checksum, DependsOn, Manifest, ManifestMetadata, Node, NodeConfig, NodeId, TestMetadata,
-    UniqueKey,
+    Checksum, DependsOn, Manifest, ManifestMetadata, Node, NodeConfig, NodeId, SourceNode,
+    TestMetadata, UniqueKey,
 };
 pub use path::{match_changed_path, normalize_path};
 pub use pr_diff::{
diff --git a/tests/fixtures/MANIFEST.toml b/tests/fixtures/MANIFEST.toml
index a198c3dc..956a10b4 100644
--- a/tests/fixtures/MANIFEST.toml
+++ b/tests/fixtures/MANIFEST.toml
@@ -208,6 +208,29 @@ with engine-extracted body_leaf_table_refs). Pure synthetic data only; \
 the `messy_shop` package name and node names are fictitious.\
 """
 
+[[fixture]]
+path = "ref-and-source-import-cte.json"
+origin = "synthetic-handcrafted"
+origin_url = "https://github.com/breezy-bays-labs/cute-dbt/issues/57"
+sha256 = "459074a1f145aaf14bcf72210d3a7d050df7e6df06f66df4871e77a7874a3a92"
+synthetic_only = true
+synthetic_handcrafted = true
+license = "Apache-2.0"
+description = """
+Synthetic single-model manifest exercising source() given binding \
+(cute-dbt#57). The `stg_mixed` model carries BOTH a ref()-based import \
+CTE (`orders`) and a source()-based import CTE (`patients`); its unit \
+test mocks both inputs. The top-level `sources` block carries two \
+entries in the two engine dialects the #145 rule demands: the bound \
+`demo_raw.patients` entry in dbt-core style (explicit `null` for unset \
+optional keys) and a `demo_raw.encounters` entry in dbt-fusion style \
+(unset keys omitted entirely). The renderer must bind the ref() given \
+to `orders` directly and the source() given to `patients` by resolving \
+(source_name, name) through the sources map to the physical identifier \
+matched against the CTE body leaf. Pure synthetic data only; the \
+`mixed_shop` package, the names, and the rows are fictitious.\
+"""
+
 [[fixture]]
 path = "fusion-csv-raw-string.json"
 origin = "synthetic-handcrafted"
diff --git a/tests/fixtures/ref-and-source-import-cte.json b/tests/fixtures/ref-and-source-import-cte.json
new file mode 100644
index 00000000..1ae10063
--- /dev/null
+++ b/tests/fixtures/ref-and-source-import-cte.json
@@ -0,0 +1,95 @@
+{
+  "metadata": {
+    "dbt_schema_version": "https://schemas.getdbt.com/dbt/manifest/v12.json",
+    "dbt_version": "1.11.9",
+    "generated_at": "1970-01-01T00:00:00Z",
+    "invocation_id": "00000000-0000-0000-0000-000000000000",
+    "project_name": "mixed_shop",
+    "project_id": "0000000000000000000000000000000000000000",
+    "user_id": "00000000-0000-0000-0000-000000000000",
+    "send_anonymous_usage_stats": false,
+    "adapter_type": "duckdb"
+  },
+  "nodes": {
+    "model.mixed_shop.stg_mixed": {
+      "database": "mixed_shop",
+      "schema": "main",
+      "name": "stg_mixed",
+      "resource_type": "model",
+      "package_name": "mixed_shop",
+      "path": "staging/stg_mixed.sql",
+      "original_file_path": "models/staging/stg_mixed.sql",
+      "unique_id": "model.mixed_shop.stg_mixed",
+      "fqn": ["mixed_shop", "staging", "stg_mixed"],
+      "alias": "stg_mixed",
+      "checksum": {
+        "name": "sha256",
+        "checksum": "REF_AND_SOURCE_SYNTHETIC_SENTINEL_0001"
+      },
+      "raw_code": "{# Synthetic ref+source import-CTE fixture exercising source() binding (cute-dbt#57). #}\nwith orders as (\n  select * from {{ ref('raw_orders') }}\n), patients as (\n  select * from {{ source('demo_raw', 'patients') }}\n)\nselect o.order_id, p.patient_name\nfrom orders o\njoin patients p on p.patient_id = o.patient_id",
+      "compiled_code": "with orders as (\n  select * from \"mixed_shop\".\"main\".\"raw_orders\"\n), patients as (\n  select * from \"mixed_shop\".\"raw_layer\".\"patients\"\n)\nselect o.order_id, p.patient_name\nfrom orders o\njoin patients p on p.patient_id = o.patient_id",
+      "depends_on": {
+        "nodes": [
+          "model.mixed_shop.raw_orders",
+          "source.mixed_shop.demo_raw.patients"
+        ]
+      }
+    }
+  },
+  "sources": {
+    "source.mixed_shop.demo_raw.patients": {
+      "database": "mixed_shop",
+      "schema": "raw_layer",
+      "name": "patients",
+      "resource_type": "source",
+      "package_name": "mixed_shop",
+      "unique_id": "source.mixed_shop.demo_raw.patients",
+      "source_name": "demo_raw",
+      "identifier": "patients",
+      "relation_name": "\"mixed_shop\".\"raw_layer\".\"patients\"",
+      "loaded_at_field": null,
+      "loaded_at_query": null,
+      "freshness": null,
+      "external": null,
+      "patch_path": null
+    },
+    "source.mixed_shop.demo_raw.encounters": {
+      "schema": "raw_layer",
+      "name": "encounters",
+      "resource_type": "source",
+      "package_name": "mixed_shop",
+      "unique_id": "source.mixed_shop.demo_raw.encounters",
+      "source_name": "demo_raw"
+    }
+  },
+  "unit_tests": {
+    "unit_test.mixed_shop.test_stg_mixed_joins_ref_and_source": {
+      "name": "test_stg_mixed_joins_ref_and_source",
+      "model": "stg_mixed",
+      "package_name": "mixed_shop",
+      "resource_type": "unit_test",
+      "unique_id": "unit_test.mixed_shop.test_stg_mixed_joins_ref_and_source",
+      "original_file_path": "models/staging/_unit_tests.yml",
+      "given": [
+        {
+          "input": "ref('raw_orders')",
+          "rows": [{"order_id": 1, "patient_id": 7}]
+        },
+        {
+          "input": "source('demo_raw', 'patients')",
+          "rows": [{"patient_id": 7, "patient_name": "Synthetic Sam"}]
+        }
+      ],
+      "expect": {
+        "rows": [
+          {"order_id": 1, "patient_name": "Synthetic Sam"}
+        ]
+      },
+      "description": "Synthetic ref+source binding case: the ref() given must bind to the `orders` import CTE and the source() given must bind to the `patients` import CTE via the manifest sources block (cute-dbt#57).",
+      "config": {
+        "tags": [],
+        "meta": {}
+      }
+    }
+  }
+}
diff --git a/tests/headless_toggle.rs b/tests/headless_toggle.rs
index de8fd25c..39e447bf 100644
--- a/tests/headless_toggle.rs
+++ b/tests/headless_toggle.rs
@@ -48,8 +48,9 @@ use cute_dbt::adapters::render::{
 use cute_dbt::domain::{
     BlockDiff, Checksum, DEFAULT_REPORT_TITLE, DependsOn, DiffLine, DiffLineKind, FileHunks, Hunk,
     InScopeSet, Manifest, ManifestMetadata, ModelInScopeSet, Node, NodeConfig, NodeId,
-    NormalizedDiffIndex, PrDiff, TestMetadata, UnitTest, UnitTestDataDiff, UnitTestExpect,
-    UnitTestGiven, UnitTestYamlBlock, external_fixture_table, reconstruct_table_diffs,
+    NormalizedDiffIndex, PrDiff, SourceNode, TestMetadata, UnitTest, UnitTestDataDiff,
+    UnitTestExpect, UnitTestGiven, UnitTestYamlBlock, external_fixture_table,
+    reconstruct_table_diffs,
 };
 use cute_dbt::ports::ManifestSource;
 
@@ -4160,6 +4161,127 @@ fn self_named_import_cte_renders_distinct_dag_nodes_not_a_cycle() {
     let _ = tab.close(true);
 }
 
+// --- cute-dbt#57: source() given binding in the Node-detail panel -----
+
+#[test]
+#[ignore = "requires Chrome; runs explicitly in the headless-zero-egress CI job via `-- --ignored`"]
+fn source_given_fixture_card_renders_in_the_node_detail_panel() {
+    // cute-dbt#57 end-to-end DOM proof: a `given: source('synthea_raw',
+    // 'patients')` resolves through the manifest sources block to the
+    // physical identifier, binds to the `source` import CTE, and the
+    // Node-detail panel renders the given's fixture card (NOT the
+    // "no fixture provided" empty-state) when that node is clicked.
+    let model = model_node_with_compiled(
+        "model.shop.stg_patients",
+        "with source as (select * from \"memory\".\"main\".\"patients\") \
+         select id, name from source",
+    );
+    let ut = UnitTest::new(
+        "t".to_owned(),
+        NodeId::new("stg_patients"),
+        vec![UnitTestGiven::new(
+            "source('synthea_raw', 'patients')".to_owned(),
+            serde_json::json!([{"id": 1, "name": "Synthetic Sam"}]),
+            Some("dict".to_owned()),
+            None,
+        )],
+        UnitTestExpect::new(serde_json::Value::Null, None, None),
+        None,
+        DependsOn::default(),
+        None,
+        None,
+        None,
+    );
+    let source = SourceNode::new(
+        NodeId::new("source.shop.synthea_raw.patients"),
+        "synthea_raw",
+        "patients",
+        Some("patients".to_owned()),
+        "main",
+        Some("memory".to_owned()),
+        Some("\"memory\".\"main\".\"patients\"".to_owned()),
+    );
+    let m = manifest(vec![model], vec![("unit_test.shop.stg_patients.t", ut)])
+        .with_sources(std::iter::once((source.id().clone(), source)).collect());
+    let in_scope: InScopeSet =
+        std::iter::once("unit_test.shop.stg_patients.t".to_owned()).collect();
+    let models: ModelInScopeSet = std::iter::once(NodeId::new("model.shop.stg_patients")).collect();
+    let out = tmp("headless_source_given_binding.html");
+    let _ = std::fs::remove_file(&out);
+    render_report(
+        &out,
+        &m,
+        &in_scope,
+        &models,
+        &InScopeSet::new(),
+        &HashMap::new(),
+        &HashMap::new(),
+        &HashMap::new(),
+        &HashMap::new(),
+        "baseline.json",
+        ScopeSource::Baseline,
+        DEFAULT_REPORT_TITLE,
+        None,
+    )
+    .expect("render writes the report");
+    let url = format!(
+        "file://{}",
+        out.to_str().expect("report path is valid UTF-8")
+    );
+
+    let browser = launch_browser();
+    let tab = browser.new_tab().expect("new tab");
+    tab.navigate_to(&url)
+        .expect("navigate source-binding report");
+    tab.wait_until_navigated().expect("await navigation");
+    tab.wait_for_element_with_custom_timeout(
+        ".cte-dag-mermaid svg",
+        std::time::Duration::from_secs(15),
+    )
+    .expect("Mermaid DAG SVG renders");
+
+    // Click the import CTE node (named `source` — dbt's unwrapper
+    // convention) and read its Node-detail panel.
+    let clicked = eval_bool(
+        &tab,
+        "(function(){var g=document.querySelector('.cte-dag-mermaid svg g.node[data-node-id=\"source\"]');\
+          if(!g){return false;}g.dispatchEvent(new MouseEvent('click',{bubbles:true}));return true;})()",
+    );
+    assert!(
+        clicked,
+        "the `source` import CTE node is present + clickable"
+    );
+
+    let card_input = eval_string(
+        &tab,
+        "(document.querySelector('.node-detail .given-section')||{getAttribute:function(){return ''}})\
+         .getAttribute('data-input-name')||''",
+    );
+    assert_eq!(
+        card_input, "source('synthea_raw', 'patients')",
+        "the bound source() given renders its fixture card in the Node-detail panel",
+    );
+    let has_empty_state = eval_bool(
+        &tab,
+        "!!document.querySelector('.node-detail .given-empty')",
+    );
+    assert!(
+        !has_empty_state,
+        "a bound source() given must not show the no-fixture empty-state copy",
+    );
+    // The fixture rows actually render in the card's grid.
+    let card_text = eval_string(
+        &tab,
+        "(document.querySelector('.node-detail .given-section')||{}).textContent||''",
+    );
+    assert!(
+        card_text.contains("Synthetic Sam"),
+        "the given's mocked rows render inside the fixture card: {card_text}",
+    );
+
+    let _ = tab.close(true);
+}
+
 // --- cute-dbt#157: mobile viewport blowout on the stacked panel -------
 
 /// Build `n_rows` JSON dict rows each with `n_cols` columns of long,
diff --git a/tests/render_integration.rs b/tests/render_integration.rs
index 4459cf2d..c1b60b4b 100644
--- a/tests/render_integration.rs
+++ b/tests/render_integration.rs
@@ -15,8 +15,12 @@ use cute_dbt::adapters::asset_embed::{
     CYTOSCAPE_JS, DATATABLES_CSS, DATATABLES_JS, JQUERY_JS, MERMAID_JS, SAKURA_CSS,
 };
 use cute_dbt::adapters::manifest::FileManifestSource;
-use cute_dbt::adapters::render::{ScopeSource, column_meta_for_model, render_report};
-use cute_dbt::domain::{DEFAULT_REPORT_TITLE, Manifest, NodeId, StateComparator};
+use cute_dbt::adapters::render::{
+    ScopeSource, build_payload, column_meta_for_model, render_report,
+};
+use cute_dbt::domain::{
+    DEFAULT_REPORT_TITLE, InScopeSet, Manifest, ModelInScopeSet, NodeId, StateComparator,
+};
 use cute_dbt::ports::ManifestSource;
 
 /// Absolute path to a committed fixture under `tests/fixtures/`.
@@ -368,3 +372,118 @@ fn column_meta_matches_the_handoff_mapping_against_the_real_fusion_fixture() {
     );
     assert!(rel.values.is_empty(), "relationships carries no pills");
 }
+
+#[test]
+fn source_given_binds_end_to_end_from_a_committed_fixture() {
+    // cute-dbt#57 vertical, file → Stage-1 preflight → sources block →
+    // payload binding: the committed synthetic fixture carries a model
+    // with BOTH a ref()-based import CTE and a source()-based import
+    // CTE, plus a two-dialect `sources` block (core-style explicit
+    // nulls AND fusion-style absent keys — the #145 rule).
+    let current = load("ref-and-source-import-cte.json");
+
+    // The adapter parsed both dialects of the sources block.
+    assert_eq!(current.sources().len(), 2);
+    let patients = current
+        .source_by_name("demo_raw", "patients")
+        .expect("the core-style (explicit-null) source entry resolves");
+    assert_eq!(
+        patients.relation_name(),
+        Some("\"mixed_shop\".\"raw_layer\".\"patients\"")
+    );
+    let encounters = current
+        .source_by_name("demo_raw", "encounters")
+        .expect("the fusion-style (absent-key) source entry resolves");
+    assert!(encounters.identifier().is_none());
+    assert!(encounters.relation_name().is_none());
+
+    // The render payload binds each given to its own import CTE.
+    let test_id = "unit_test.mixed_shop.test_stg_mixed_joins_ref_and_source";
+    let model_id = NodeId::new("model.mixed_shop.stg_mixed");
+    let in_scope = InScopeSet::from_iter([test_id.to_owned()]);
+    let models = ModelInScopeSet::from_iter([model_id]);
+    let payload = build_payload(
+        &current,
+        &in_scope,
+        &models,
+        &HashMap::new(),
+        &HashMap::new(),
+        &HashMap::new(),
+        &HashMap::new(),
+        "baseline",
+    );
+    let test = &payload.models[0].tests[0];
+    assert_eq!(
+        test.given[0].bound_to_node.as_deref(),
+        Some("orders"),
+        "ref('raw_orders') binds to the ref-based import CTE",
+    );
+    assert_eq!(
+        test.given[1].bound_to_node.as_deref(),
+        Some("patients"),
+        "source('demo_raw','patients') binds to the source-based import CTE \
+         via the manifest sources block",
+    );
+}
+
+#[test]
+fn source_given_binds_against_the_real_playground_fixture() {
+    // cute-dbt#57 REAL-fixture proof (the fusion-rule's "verify vs a real
+    // committed fixture, not just synthetic JSON"): the playground's
+    // dbt-core-1.11-compiled manifest carries
+    // `test_stg_synthea__patients_renames_and_hashes_source_columns` with
+    // `given: input: source('synthea_raw', 'patients')` on a staging
+    // model whose compiled body is the canonical unwrapper shape
+    // `with source as (select * from "memory"."main"."patients")`. The
+    // given must bind to the `source` import CTE through the manifest
+    // sources block — real engine wire, no hand-rolled shapes.
+    let current = load("playground-current.json");
+
+    // The real sources block parsed (16 synthea_raw entries) and the
+    // bound entry resolves by its authored (source_name, name) pair.
+    let patients = current
+        .source_by_name("synthea_raw", "patients")
+        .expect("the real playground sources block carries synthea_raw.patients");
+    assert_eq!(patients.identifier(), Some("patients"));
+    assert_eq!(
+        patients.relation_name(),
+        Some("\"memory\".\"main\".\"patients\""),
+        "dbt-core emits the fully-quoted three-part relation",
+    );
+
+    let test_id = "unit_test.healthcare_analytics.stg_synthea__patients.\
+                   test_stg_synthea__patients_renames_and_hashes_source_columns";
+    let model_id = NodeId::new("model.healthcare_analytics.stg_synthea__patients");
+    let unit_test = current
+        .unit_test(test_id)
+        .expect("the real playground fixture carries the source-given unit test");
+    let source_ordinal = unit_test
+        .given()
+        .iter()
+        .position(|g| g.input() == "source('synthea_raw', 'patients')")
+        .expect("the unit test declares the source('synthea_raw', 'patients') given");
+
+    let in_scope = InScopeSet::from_iter([test_id.to_owned()]);
+    let models = ModelInScopeSet::from_iter([model_id]);
+    let payload = build_payload(
+        &current,
+        &in_scope,
+        &models,
+        &HashMap::new(),
+        &HashMap::new(),
+        &HashMap::new(),
+        &HashMap::new(),
+        "baseline",
+    );
+    let test = payload.models[0]
+        .tests
+        .iter()
+        .find(|t| t.id == test_id)
+        .expect("the payload carries the source-given unit test");
+    assert_eq!(
+        test.given[source_ordinal].bound_to_node.as_deref(),
+        Some("source"),
+        "the real source('synthea_raw','patients') given binds to the \
+         `source` import CTE via the sources-block resolution",
+    );
+}