diff --git a/plugins/nemo-experimentalist/AGENTS.md b/plugins/nemo-experimentalist/AGENTS.md
index 8cbeb1fbd2..446983c654 100644
--- a/plugins/nemo-experimentalist/AGENTS.md
+++ b/plugins/nemo-experimentalist/AGENTS.md
@@ -72,9 +72,11 @@ instead of restoring Curator imports, configuration, or aliases. The obsolete
   Configure Platform services, trace storage, and Insights analysis according
   to the Platform documentation; this repository does not own a service,
   scheduler, or testbed setup.
-- `nooa` is pinned to a tagged public GitHub release in `pyproject.toml`.
-  Update the tag and lock file together. Keep the Platform-supplied Insights
-  plugin separate.
+- `nooa` is pinned to an immutable public GitHub revision in `pyproject.toml`,
+  currently a commit rather than a tag because the MCP transport-timeout fix
+  landed after `v0.0.6`. Update the revision, the matching pin in
+  `examples/tau3-nooa-agent/pyproject.toml`, and both lock files together. Keep
+  the Platform-supplied Insights plugin separate.
 - This branch uses merged Platform PR 718 contracts only. After the Platform
   handoff lands, rebase and repin before adopting any new Platform testbed or
   installer interfaces.
diff --git a/plugins/nemo-experimentalist/README.md b/plugins/nemo-experimentalist/README.md
index 95ed0b91c0..4ccd8c7f72 100644
--- a/plugins/nemo-experimentalist/README.md
+++ b/plugins/nemo-experimentalist/README.md
@@ -28,8 +28,8 @@ export NEMO=/path/to/nemo-platform/.venv/bin/nemo
 ```
 
 The source dependencies are pinned to tagged or immutable revisions in
-`pyproject.toml`. NVIDIA-labs OO Agents (NOOA) is pinned to its public
-GitHub `v0.0.6` release.
+`pyproject.toml`. NVIDIA-labs OO Agents (NOOA) is pinned to a public GitHub
+commit, currently one past `v0.0.6` that carries an MCP transport-timeout fix.
 
 ## Insight-to-experiment flow
 
diff --git a/plugins/nemo-experimentalist/benchmarks/README.md b/plugins/nemo-experimentalist/benchmarks/README.md
index 54d5020d8d..8c8fc158fe 100644
--- a/plugins/nemo-experimentalist/benchmarks/README.md
+++ b/plugins/nemo-experimentalist/benchmarks/README.md
@@ -1,13 +1,20 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# Canonical Experimentalist benchmark
+# Canonical Experimentalist benchmarks
 
-This benchmark measures M2 Experimentalist optimization on Harbor's unmodified
-Terminal-Bench 2.1 package. It does not cover M1 Insight → Eval Author behavior
-or Tau2's interactive domains.
+These benchmarks measure M2 Experimentalist optimization on unmodified Harbor Hub
+packages. They do not cover M1 Insight → Eval Author behavior.
 
-## Provenance
+Two suites ship today. Both store only task IDs and download task definitions into
+a local cache; no task content is vendored here.
+
+| Suite | Package | Tasks | Agent under test |
+| --- | --- | --- | --- |
+| `suites/terminal-bench-2.1.yaml` (default) | `terminal-bench/terminal-bench-2-1@6` | 89 | `examples/terminal-bench-agent` |
+| `suites/tau3-banking.yaml` | `sierra-research/tau3-bench@1`, banking scoped | 97 | `examples/tau3-nooa-agent` |
+
+## Terminal-Bench provenance
 
 The suite uses `terminal-bench/terminal-bench-2-1@6` from Harbor Hub:
 
@@ -17,9 +24,6 @@ The suite uses `terminal-bench/terminal-bench-2-1@6` from Harbor Hub:
 - Harbor Hub record:
   <https://hub.harborframework.com/datasets/terminal-bench/terminal-bench-2-1/6>
 
-The repository stores only task IDs. Task definitions are downloaded into a
-local cache and are never vendored here.
-
 The 38/25/26 quality partition and 35/12/12 fast partition came from Gaia's
 `optimization-datasets` commit
 `1b7688ad257dacd1a3267dddb88db6cefdc31376`. The manifest corrects
@@ -27,11 +31,34 @@ The 38/25/26 quality partition and 35/12/12 fast partition came from Gaia's
 the runner asks Harbor Hub for revision 6, verifies its content hash, and
 asserts that the quality partition covers all 89 canonical IDs exactly once.
 
+## tau3 banking provenance
+
+The suite scopes `sierra-research/tau3-bench@1` to its `banking_knowledge` domain:
+
+- 97 of the package's 375 tasks, selected by the
+  `tau3-bench__tau3-banking_knowledge-` task-ID prefix
+- dataset content hash
+  `sha256:a57304f682894ac061090769af771a3617664f3ff6e5417d4eadf8e30433e4d9`
+- Harbor Hub record:
+  <https://hub.harborframework.com/datasets/sierra-research/tau3-bench/1>
+
+The 41/28/28 quality partition came from `optimization-datasets`
+`feat/tau2-other-domains` commit `025ecd2ef2b518ad81f6b22d3f3937af8906fb01`,
+whose `tau2-banking-knowledge-NNN` names map onto the canonical
+`tau3-bench__tau3-banking_knowledge-task-NNN` IDs. The 6/3/3 fast partition draws
+only from the 87 tasks whose `reward_basis` is pure database state, so smoke runs
+score deterministically without an LLM judge.
+
+Each task also runs a `tau3-runtime` sidecar hosting the tau2 environment and user
+simulator. Tau-style suites set `models.user_simulator`, which makes the runner
+export `OPENAI_API_KEY`, `OPENAI_BASE_URL`, `TAU2_USER_MODEL`, and
+`TAU2_NL_ASSERTIONS_MODEL` for the sidecar and the verifier.
+
 ## Held-out evaluation
 
 The runner:
 
-1. evaluates the unchanged LangChain baseline on the test split;
+1. evaluates the unchanged baseline agent on the test split;
 2. gives only train and validation IDs to `run_experimentalist`;
 3. resolves the validation-selected winner from the Experimentalist run;
 4. evaluates that winner on the same test IDs and number of attempts.
@@ -52,7 +79,7 @@ export INFERENCE_API_KEY=...
 ```
 
 `EXPERIMENTALIST_API_KEY` may be provided instead. The runner maps either credential
-to both the LangChain AUT and optimizer, using
+to both the AUT and optimizer, using
 `https://inference-api.nvidia.com/v1` unless an API base is explicitly set.
 
 Validate provenance and task IDs without Docker or model calls:
@@ -65,20 +92,28 @@ Run the bounded fast benchmark:
 
 ```bash
 uv run python benchmarks/run.py \
-  --config benchmarks/configs/smoke.yaml
+  --config benchmarks/configs/terminal-bench-smoke.yaml
 ```
 
 Run the reproducible quality benchmark:
 
 ```bash
 uv run python benchmarks/run.py \
-  --config benchmarks/configs/quality.yaml
+  --config benchmarks/configs/terminal-bench-quality.yaml
+```
+
+A non-default suite needs its own suite, config, and agent:
+
+```bash
+uv run python benchmarks/run.py \
+  --suite benchmarks/suites/tau3-banking.yaml \
+  --config benchmarks/configs/tau3-smoke.yaml \
+  --agent examples/tau3-nooa-agent
 ```
 
-Both setup and agent execution require network access. The AUT installs a
-checksum-pinned static `uv`, uv-managed Python 3.12, and dependencies from its
-committed `uv.lock` directly in each canonical task container. It does not need
-the image's system Python, package manager, a sidecar, or a Docker socket.
+Both setup and agent execution require network access. Each AUT installs its own
+dependencies from its committed `uv.lock` inside the task container and does not
+need a Docker socket.
 
 Pass the same `--output` directory to resume interrupted Harbor jobs. Use a new
 output directory for an intentionally fresh run.
diff --git a/plugins/nemo-experimentalist/benchmarks/configs/tau3-quality.yaml b/plugins/nemo-experimentalist/benchmarks/configs/tau3-quality.yaml
new file mode 100644
index 0000000000..ae953389a3
--- /dev/null
+++ b/plugins/nemo-experimentalist/benchmarks/configs/tau3-quality.yaml
@@ -0,0 +1,34 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+suite_partition: quality
+test_attempts: 3
+models:
+  aut: openai/openai/openai/gpt-5-mini
+  experimentalist_smart: openai/openai/openai/gpt-5-mini
+  experimentalist_mid: openai/openai/openai/gpt-5-mini
+  experimentalist_fast: openai/openai/openai/gpt-5-mini
+  user_simulator: openai/openai/openai/gpt-5-mini
+optimizer:
+  max_rounds: 3
+  min_rounds_before_stopping: 2
+  max_survivors: 2
+  max_candidates: 3
+  max_trajectory_tasks: 8
+  max_train_batch_tasks: 16
+  train_batch_seed: 20260727
+  disable_trajectory_scoring: false
+  disable_convergence_check: false
+  evaluator:
+    n_attempts: 2
+    # Keep at 3 or lower: each task requests 8192 MB and parallel image builds
+    # have triggered Docker Hub rate limiting and DNS failures.
+    n_concurrent_trials: 3
+    quiet: true
+    agent_setup_timeout_multiplier: 2.0
+    # tau3 builds two images per task, and the first build clones and installs
+    # tau2-bench (observed 2m36s cold, 26s warm).
+    environment_build_timeout_multiplier: 3.0
+  eval_author:
+    max_traces: 10
+    max_validation_repair_attempts: 5
diff --git a/plugins/nemo-experimentalist/benchmarks/configs/tau3-smoke.yaml b/plugins/nemo-experimentalist/benchmarks/configs/tau3-smoke.yaml
new file mode 100644
index 0000000000..c4be604fb3
--- /dev/null
+++ b/plugins/nemo-experimentalist/benchmarks/configs/tau3-smoke.yaml
@@ -0,0 +1,32 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+suite_partition: fast
+test_attempts: 1
+models:
+  aut: openai/openai/openai/gpt-5-mini
+  experimentalist_smart: openai/openai/openai/gpt-5-mini
+  experimentalist_mid: openai/openai/openai/gpt-5-mini
+  experimentalist_fast: openai/openai/openai/gpt-5-mini
+  user_simulator: openai/openai/openai/gpt-5-mini
+optimizer:
+  max_rounds: 1
+  min_rounds_before_stopping: 1
+  max_survivors: 1
+  max_candidates: 1
+  max_trajectory_tasks: 2
+  max_train_batch_tasks: 4
+  train_batch_seed: 20260727
+  disable_trajectory_scoring: true
+  disable_convergence_check: true
+  evaluator:
+    n_attempts: 1
+    n_concurrent_trials: 1
+    quiet: true
+    agent_setup_timeout_multiplier: 2.0
+    # tau3 builds two images per task, and the first build clones and installs
+    # tau2-bench (observed 2m36s cold, 26s warm).
+    environment_build_timeout_multiplier: 3.0
+  eval_author:
+    max_traces: 3
+    max_validation_repair_attempts: 2
diff --git a/plugins/nemo-experimentalist/benchmarks/configs/quality.yaml b/plugins/nemo-experimentalist/benchmarks/configs/terminal-bench-quality.yaml
similarity index 100%
rename from plugins/nemo-experimentalist/benchmarks/configs/quality.yaml
rename to plugins/nemo-experimentalist/benchmarks/configs/terminal-bench-quality.yaml
diff --git a/plugins/nemo-experimentalist/benchmarks/configs/smoke.yaml b/plugins/nemo-experimentalist/benchmarks/configs/terminal-bench-smoke.yaml
similarity index 100%
rename from plugins/nemo-experimentalist/benchmarks/configs/smoke.yaml
rename to plugins/nemo-experimentalist/benchmarks/configs/terminal-bench-smoke.yaml
diff --git a/plugins/nemo-experimentalist/benchmarks/run.py b/plugins/nemo-experimentalist/benchmarks/run.py
index 889a696f0a..2fe7d2e0a1 100644
--- a/plugins/nemo-experimentalist/benchmarks/run.py
+++ b/plugins/nemo-experimentalist/benchmarks/run.py
@@ -1,7 +1,7 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-"""Run the canonical Terminal-Bench Experimentalist benchmark."""
+"""Run a canonical Experimentalist benchmark suite."""
 
 import argparse
 import asyncio
@@ -32,7 +32,7 @@
 PLUGIN_ROOT = Path(__file__).resolve().parents[1]
 BENCHMARK_ROOT = Path(__file__).resolve().parent
 DEFAULT_SUITE = BENCHMARK_ROOT / "suites" / "terminal-bench-2.1.yaml"
-DEFAULT_CONFIG = BENCHMARK_ROOT / "configs" / "smoke.yaml"
+DEFAULT_CONFIG = BENCHMARK_ROOT / "configs" / "terminal-bench-smoke.yaml"
 DEFAULT_AGENT = PLUGIN_ROOT / "examples" / "terminal-bench-agent"
 DEFAULT_DATASET_CACHE = PLUGIN_ROOT / "tmp" / "benchmark-datasets"
 DEFAULT_RUNTIME_CACHE = PLUGIN_ROOT / "tmp" / "runtime-cache"
@@ -45,6 +45,7 @@ class CanonicalDatasetSpec(BaseModel):
     registry_url: str
     source_url: str
     expected_task_count: int = Field(gt=0)
+    task_id_prefix: str | None = None
 
     @property
     def requested_reference(self) -> str:
@@ -88,6 +89,36 @@ class SuiteSpec(BaseModel):
     schema_version: Literal[1]
     dataset: CanonicalDatasetSpec
     partitions: PartitionsSpec
+    workspace: str
+    framework_skills: list[str] = Field(min_length=1)
+
+    @model_validator(mode="after")
+    def expand_partition_task_ids(self) -> Self:
+        """Read partition entries as names inside the suite's ``task_id_prefix``.
+
+        Every ID in a domain-scoped package repeats that prefix, which buries the part
+        that differs. Manifests write the distinguishing name and the prefix is joined
+        back on here, so the rest of the runner still works in canonical IDs. A manifest
+        that writes full IDs anyway fails the quality-coverage check with both forms in
+        the message.
+        """
+        prefix = self.dataset.task_id_prefix
+        if prefix is None:
+            return self
+        for split in (self.partitions.quality, self.partitions.fast):
+            for role in ("train", "validation", "test"):
+                setattr(split, role, [f"{prefix}{name}" for name in getattr(split, role)])
+        return self
+
+    def framework_skills_dirs(self, plugin_root: Path) -> list[Path]:
+        """Resolve framework-skill names to directories, failing on unknown names."""
+        dirs: list[Path] = []
+        for name in self.framework_skills:
+            path = plugin_root / "framework-skills" / name
+            if not path.is_dir():
+                raise ValueError(f"Unknown framework skill {name!r}: {path} is not a directory")
+            dirs.append(path)
+        return dirs
 
 
 class ModelSpec(BaseModel):
@@ -95,6 +126,7 @@ class ModelSpec(BaseModel):
     experimentalist_smart: str
     experimentalist_mid: str
     experimentalist_fast: str
+    user_simulator: str | None = None
 
 
 class BenchmarkConfig(BaseModel):
@@ -126,13 +158,23 @@ def validate_canonical_suite(
     *,
     canonical_task_ids: set[str],
     resolved_ref: str,
-) -> None:
-    """Verify immutable revision, quality coverage, and all partition IDs."""
+) -> set[str]:
+    """Verify immutable revision, quality coverage, and all partition IDs.
+
+    Returns the canonical task IDs scoped to this suite's domain. When the suite
+    sets ``task_id_prefix``, the package may hold other domains; coverage is then
+    enforced against the matching subset rather than the whole package.
+    """
     if resolved_ref != suite.dataset.resolved_ref:
         raise ValueError(
             f"Dataset {suite.dataset.requested_reference} resolved to {resolved_ref}, "
             f"expected {suite.dataset.resolved_ref}"
         )
+    prefix = suite.dataset.task_id_prefix
+    if prefix is not None:
+        canonical_task_ids = {task_id for task_id in canonical_task_ids if task_id.startswith(prefix)}
+        if not canonical_task_ids:
+            raise ValueError(f"No canonical tasks match task_id_prefix {prefix!r}")
     if len(canonical_task_ids) != suite.dataset.expected_task_count:
         raise ValueError(
             f"Canonical dataset has {len(canonical_task_ids)} tasks, expected {suite.dataset.expected_task_count}"
@@ -147,6 +189,7 @@ def validate_canonical_suite(
     unknown_fast = sorted(set(suite.partitions.fast.all_ids()) - canonical_task_ids)
     if unknown_fast:
         raise ValueError(f"Fast partition contains unknown canonical task IDs: {unknown_fast}")
+    return canonical_task_ids
 
 
 def _configure_models(models: ModelSpec) -> None:
@@ -164,6 +207,16 @@ def _configure_models(models: ModelSpec) -> None:
     os.environ["EXPERIMENTALIST_MID_MODEL_NAME"] = models.experimentalist_mid
     os.environ["EXPERIMENTALIST_FAST_MODEL_NAME"] = models.experimentalist_fast
     os.environ.setdefault("NEMO_EXPERIMENTALIST_RUNTIME_CACHE", str(DEFAULT_RUNTIME_CACHE))
+    if models.user_simulator is not None:
+        # tau-style tasks run a user simulator and NL-assertion judge inside the task
+        # environment, which read OpenAI-style variables and need the /v1 suffix.
+        # Assigned rather than setdefault: an ambient OPENAI_API_KEY from the developer's
+        # shell would otherwise be paired with this gateway base URL and always 401.
+        trimmed_base = api_base.rstrip("/")
+        os.environ["OPENAI_API_KEY"] = api_key
+        os.environ["OPENAI_BASE_URL"] = trimmed_base if trimmed_base.endswith("/v1") else f"{trimmed_base}/v1"
+        os.environ["TAU2_USER_MODEL"] = models.user_simulator
+        os.environ["TAU2_NL_ASSERTIONS_MODEL"] = models.user_simulator
 
 
 def _agent_digest(agent_dir: Path) -> str:
@@ -342,7 +395,12 @@ async def run_benchmark(args: argparse.Namespace) -> Path:
     package_client = PackageDatasetClient()
     metadata = await package_client.get_dataset_metadata(suite.dataset.requested_reference)
     canonical_task_ids = {task.name for task in metadata.task_ids}
-    validate_canonical_suite(suite, canonical_task_ids=canonical_task_ids, resolved_ref=metadata.version)
+    canonical_task_ids = validate_canonical_suite(
+        suite, canonical_task_ids=canonical_task_ids, resolved_ref=metadata.version
+    )
+    # Resolved up front: the optimizer only needs these after the baseline evaluation,
+    # which is hours of image builds to discover a typo'd skill name.
+    framework_skills_dirs = suite.framework_skills_dirs(PLUGIN_ROOT)
 
     if args.validate_only:
         print(
@@ -397,10 +455,10 @@ async def run_benchmark(args: argparse.Namespace) -> Path:
             metadata={"id": f"{benchmark_config.suite_partition}-validation", "task_ids": split.validation},
         ),
         experiment_dir=experimentalist_dir,
-        workspace="canonical-terminal-bench-2-1",
+        workspace=suite.workspace,
         client=None,
         config=benchmark_config.optimizer,
-        framework_skills_dirs=[PLUGIN_ROOT / "framework-skills" / "langchain-framework"],
+        framework_skills_dirs=framework_skills_dirs,
     )
     run_document = json.loads((experimentalist_dir / "eval-and-optimize" / "run.json").read_text(encoding="utf-8"))
     winner_label = run_document.get("winner_agent")
diff --git a/plugins/nemo-experimentalist/benchmarks/suites/tau3-banking.yaml b/plugins/nemo-experimentalist/benchmarks/suites/tau3-banking.yaml
new file mode 100644
index 0000000000..456612a219
--- /dev/null
+++ b/plugins/nemo-experimentalist/benchmarks/suites/tau3-banking.yaml
@@ -0,0 +1,50 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+schema_version: 1
+dataset:
+  name: sierra-research/tau3-bench
+  ref: "1"
+  resolved_ref: sha256:a57304f682894ac061090769af771a3617664f3ff6e5417d4eadf8e30433e4d9
+  registry_url: https://hub.harborframework.com
+  source_url: https://hub.harborframework.com/datasets/sierra-research/tau3-bench/1
+  expected_task_count: 97
+  task_id_prefix: tau3-bench__tau3-banking_knowledge-
+workspace: canonical-tau3-banking
+framework_skills:
+  - nooa
+partitions:
+  source:
+    commit: 025ecd2ef2b518ad81f6b22d3f3937af8906fb01
+    note: >-
+      The commit above identifies the `optimization-datasets`
+      `feat/tau2-other-domains` revision these train/validation/test splits were
+      derived from. Its `tau2-banking-knowledge-NNN` directory names map onto the
+      canonical `tau3-bench__tau3-banking_knowledge-task-NNN` IDs. Task IDs only;
+      no task content is copied here. The fast partition draws only from the 87
+      tasks whose reward basis is pure database state, so smoke runs need no LLM
+      judge.
+  quality:
+    train: [
+      task-001, task-002, task-003, task-008, task-010, task-012, task-018, task-019, task-020,
+      task-025, task-026, task-027, task-033, task-034, task-035, task-040, task-041, task-043,
+      task-048, task-049, task-050, task-055, task-056, task-057, task-062, task-063, task-064,
+      task-069, task-070, task-071, task-076, task-077, task-078, task-083, task-084, task-085,
+      task-090, task-091, task-092, task-097, task-098
+    ]
+    validation: [
+      task-004, task-005, task-014, task-015, task-021, task-022, task-028, task-029, task-036,
+      task-037, task-044, task-045, task-051, task-052, task-058, task-059, task-065, task-066,
+      task-072, task-073, task-079, task-080, task-086, task-087, task-093, task-094, task-100,
+      task-101
+    ]
+    test: [
+      task-006, task-007, task-016, task-017, task-023, task-024, task-031, task-032, task-038,
+      task-039, task-046, task-047, task-053, task-054, task-060, task-061, task-067, task-068,
+      task-074, task-075, task-081, task-082, task-088, task-089, task-095, task-096, task-099,
+      task-102
+    ]
+  fast:
+    train: [task-001, task-002, task-003, task-010, task-018, task-019]
+    validation: [task-005, task-015, task-021]
+    test: [task-006, task-007, task-016]
diff --git a/plugins/nemo-experimentalist/benchmarks/suites/terminal-bench-2.1.yaml b/plugins/nemo-experimentalist/benchmarks/suites/terminal-bench-2.1.yaml
index 55dfd569b8..14540acc32 100644
--- a/plugins/nemo-experimentalist/benchmarks/suites/terminal-bench-2.1.yaml
+++ b/plugins/nemo-experimentalist/benchmarks/suites/terminal-bench-2.1.yaml
@@ -9,6 +9,9 @@ dataset:
   registry_url: https://raw.githubusercontent.com/laude-institute/harbor/main/registry.json
   source_url: https://hub.harborframework.com/datasets/terminal-bench/terminal-bench-2-1/6
   expected_task_count: 89
+workspace: canonical-terminal-bench-2-1
+framework_skills:
+  - langchain-framework
 partitions:
   source:
     commit: 1b7688ad257dacd1a3267dddb88db6cefdc31376
diff --git a/plugins/nemo-experimentalist/examples/tau3-nooa-agent/AGENT-SPEC.md b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/AGENT-SPEC.md
new file mode 100644
index 0000000000..bc0bbbc8c8
--- /dev/null
+++ b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/AGENT-SPEC.md
@@ -0,0 +1,40 @@
+<!-- SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. -->
+<!-- SPDX-License-Identifier: Apache-2.0 -->
+
+# Customer Service Agent
+
+You are a customer service agent handling one customer conversation to completion.
+
+Your domain — the products, the tools, and the policy you must follow — is described
+in the task instruction you receive. Read it before acting. It is authoritative: where
+this document and the task instruction disagree, follow the task instruction.
+
+## Shape of the conversation
+
+Start the conversation, then read the returned state to learn which tools this domain
+offers. Alternate between listening to the customer and acting, until the request is
+resolved or you have established that you cannot resolve it. Finish only when the
+conversation is genuinely over.
+
+## Conduct
+
+**Establish facts before acting.** Look up the customer's actual records rather than
+relying on what they assert or what seems typical. Read-only tools are cheap; a wrong
+write is expensive.
+
+**Confirm before you change anything.** Before a tool call that modifies state, tell
+the customer exactly what you are about to do and get their agreement. This applies to
+each distinct change, not once for the whole conversation.
+
+**Never invent data.** Do not fabricate identifiers, balances, dates, prices, or
+policy rules. If you need a value you do not have, look it up or ask.
+
+**Respect the policy's limits.** When the policy forbids an action, say so plainly and
+explain what the customer can do instead. Do not improvise a workaround, and do not
+carry out a request just because the customer insists.
+
+**One thing at a time.** Ask for one piece of information per turn. Prefer several
+small verified steps over one large speculative one.
+
+**Handle the whole request.** A customer asking for three things needs all three
+addressed, or an explicit account of which you could not do and why.
diff --git a/plugins/nemo-experimentalist/examples/tau3-nooa-agent/README.md b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/README.md
new file mode 100644
index 0000000000..ae72feb3a5
--- /dev/null
+++ b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/README.md
@@ -0,0 +1,32 @@
+<!-- SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. -->
+<!-- SPDX-License-Identifier: Apache-2.0 -->
+
+# tau3 NOOA agent
+
+Agent under test for the tau3-bench suites. Uses [NOOA](https://github.com/NVIDIA-NeMo/labs-OO-Agents)
+with a CodeAct strategy and reaches domain tools over MCP from the task's
+`tau3-runtime` sidecar.
+
+`AGENT-SPEC.md` is deliberately domain-generic — the domain policy arrives at runtime
+in the task instruction. It is also what the Experimentalist mutates during
+optimization.
+
+A task's `[environment].env` only interpolates its docker-compose file, and upstream
+wires those variables into the `tau3-runtime` sidecar rather than into the container
+the agent runs in. `harbor_wrapper` therefore passes `OPENAI_API_KEY` and
+`OPENAI_BASE_URL` through at exec time; `INFERENCE_API_KEY` / `INFERENCE_API_BASE` are
+honored as a fallback when running `main.py` outside the wrapper.
+
+The agent raises nooa's `tool_call_timeout` to 300 seconds, overridable with
+`TAU3_MCP_TOOL_TIMEOUT_SECONDS`, because the sidecar runs a user-simulator LLM inside
+`start_conversation` and `send_message_to_user`. The default of 60 seconds would be
+enough today, but leaves no room for a slower model.
+
+Run this agent through the benchmark harness rather than invoking it directly:
+
+```bash
+uv run python benchmarks/run.py \
+  --suite benchmarks/suites/tau3-banking.yaml \
+  --config benchmarks/configs/tau3-smoke.yaml \
+  --agent examples/tau3-nooa-agent
+```
diff --git a/plugins/nemo-experimentalist/examples/tau3-nooa-agent/agent.py b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/agent.py
new file mode 100644
index 0000000000..531e883c48
--- /dev/null
+++ b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/agent.py
@@ -0,0 +1,59 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import os
+from datetime import timedelta
+
+from nooa import Agent, CodeActStrategy, strategy
+from nooa.config import CodeActConfig
+from nooa.mcp import MCPManager
+from nooa.tools import ShellTools
+from nooa.tracing import enable_tracing, exporters
+from nooa.unifiedllm import CompletionClient
+
+enable_tracing(
+    exporters=[
+        exporters.jsonl(trace_dir="/app/traces/"),
+    ]
+)
+
+# Generous because send_message_to_user blocks on the sidecar's user-simulator LLM.
+MCP_TOOL_TIMEOUT_SECONDS = float(os.environ.get("TAU3_MCP_TOOL_TIMEOUT_SECONDS", "300"))
+
+# harbor_wrapper hands OPENAI_API_KEY/OPENAI_BASE_URL to this process, matching the
+# names the tau3 task environment uses. INFERENCE_* is the fallback for running the
+# agent outside the wrapper.
+llm = CompletionClient(
+    model=os.environ.get("NEMO_AGENT_MODEL", "openai/azure/anthropic/claude-haiku-4-5"),
+    api_key=os.environ.get("OPENAI_API_KEY") or os.environ.get("INFERENCE_API_KEY"),
+    api_base=os.environ.get("OPENAI_BASE_URL")
+    or os.environ.get("INFERENCE_API_BASE", "https://inference-api.nvidia.com/v1"),
+)
+
+
+class Codeact(Agent, llm=llm):
+    def __init__(self, *args: object, **kwargs: object) -> None:
+        super().__init__(*args, **kwargs)
+        self.shell = ShellTools()
+        self.tau3_runtime = MCPManager.create_from_server(
+            "tau3-runtime",
+            url=os.environ.get("TAU3_RUNTIME_URL", "http://tau3-runtime:8000/mcp"),
+            transport="streamable-http",
+            tool_call_timeout=timedelta(seconds=MCP_TOOL_TIMEOUT_SECONDS),
+        )
+
+    @strategy(CodeActStrategy(config=CodeActConfig(max_iterations=60)))
+    async def solve(self, instruction: str) -> None:
+        """Solve the task given the instruction.
+
+        Start by calling ``await self.tau3_runtime.start_conversation()``. Use
+        the returned state and subsequent tau3-runtime tools to complete the
+        conversation before returning.
+        """
+        self.context["instruction"] = instruction
+        self.context["mcp_usage"] = (
+            "Use await self.tau3_runtime.<tool_name>(...) to call the "
+            "tau3-runtime MCP tools. Start with "
+            "await self.tau3_runtime.start_conversation()."
+        )
+        ...
diff --git a/plugins/nemo-experimentalist/examples/tau3-nooa-agent/harbor_wrapper.py b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/harbor_wrapper.py
new file mode 100644
index 0000000000..e8c364cf4d
--- /dev/null
+++ b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/harbor_wrapper.py
@@ -0,0 +1,172 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import asyncio
+import fnmatch
+import glob
+import json
+import logging
+import os
+import shlex
+import shutil
+import tempfile
+from pathlib import Path
+
+from harbor import AgentContext, BaseAgent, BaseEnvironment
+
+logger = logging.getLogger(__name__)
+
+AGENT_DIR = Path(__file__).parent
+ARTIFACTS_DIR = "/app/artifacts"
+TRACES_DIR = "/app/traces"
+COLLECTED_ARTIFACTS_DIR = "/logs/artifacts"
+UV_VERSION = "0.9.14"
+INSTALL_ATTEMPTS = 3
+# A task's [environment].env only interpolates its docker-compose file, and upstream
+# wires those variables into the tau3-runtime sidecar that hosts the user simulator and
+# the judge. The main service declares no environment of its own, so the credentials the
+# agent needs for its own model calls have to be handed over at exec time.
+MODEL_CREDENTIAL_VARS = ("OPENAI_API_KEY", "OPENAI_BASE_URL")
+
+# Artifact contract:
+# - Files intended for review/fetching must be written under /app/artifacts.
+# - Agent traces must be written under /app/traces.
+# - Verifier diagnostics should be printed by the verifier so Harbor captures them
+#   in verifier/test-stdout.txt; do not create custom diagnostic artifact files.
+# The wrapper mirrors only these locations into /logs/artifacts for Harbor collection.
+
+EXCLUDE = {
+    "eval-and-optimize",
+    "__pycache__",
+    ".git",
+    ".claude",
+    ".uv",
+    ".venv",
+    ".env",
+    "traces",
+    "artifacts",
+}
+EXCLUDE_GLOB = {"output.*"}
+
+
+class WrappedAgent(BaseAgent):
+    @staticmethod
+    def name() -> str:
+        return "nemo-experimentalist-tau3-nooa"
+
+    def version(self) -> str | None:
+        return "1.0.0"
+
+    async def setup(self, environment: BaseEnvironment) -> None:
+        """Upload agent files to the container and install dependencies."""
+        for entry in AGENT_DIR.iterdir():
+            name = entry.name
+            if name in EXCLUDE:
+                continue
+            if any(fnmatch.fnmatch(name, pat) for pat in EXCLUDE_GLOB):
+                continue
+            if entry.is_file():
+                await environment.upload_file(entry, f"/app/{name}")
+            elif entry.is_dir():
+                await environment.upload_dir(entry, f"/app/{name}")
+        # The tau3 task image is python:3.12-slim: it already has the interpreter the
+        # agent needs plus pip, but neither uv nor the curl its installer expects.
+        install = (
+            f"cd /app && pip install --no-cache-dir --quiet uv=={UV_VERSION} && UV_HTTP_TIMEOUT=300 uv sync --frozen"
+        )
+        for attempt in range(1, INSTALL_ATTEMPTS + 1):
+            proc = await environment.exec(install)
+            if proc.return_code == 0:
+                logger.info(f"[setup] {proc.stdout}")
+                return
+            logger.warning(
+                f"[setup] install attempt {attempt}/{INSTALL_ATTEMPTS} failed (rc={proc.return_code}): "
+                f"stdout={(proc.stdout or '')[-500:]} stderr={(proc.stderr or '')[-500:]}"
+            )
+            if attempt < INSTALL_ATTEMPTS:
+                await asyncio.sleep(10)
+        raise RuntimeError(
+            f"Installation failed after {INSTALL_ATTEMPTS} attempts. "
+            f"Last error (rc={proc.return_code}): {proc.stderr or proc.stdout}"
+        )
+
+    @staticmethod
+    def _parse_trace_metrics(traces_dir: str) -> dict[str, int]:
+        def token_count(attributes: dict[str, dict[str, object]], key: str) -> int:
+            value = attributes.get(key, {})
+            raw_count = value.get("intValue", value.get("doubleValue", 0))
+            if not isinstance(raw_count, int | float | str):
+                raise TypeError(f"Invalid token count for {key}: {raw_count!r}")
+            return int(raw_count)
+
+        n_input = n_output = n_cache = 0
+        paths = glob.glob(f"{traces_dir}/**/*.jsonl", recursive=True)
+        if not paths:
+            raise FileNotFoundError(f"No JSONL traces found under {traces_dir}")
+
+        for path in paths:
+            with open(path, encoding="utf-8") as trace_file:
+                for line_number, line in enumerate(trace_file, start=1):
+                    line = line.strip()
+                    if not line:
+                        continue
+                    try:
+                        data = json.loads(line)
+                        for resource_spans in data.get("resourceSpans", []):
+                            for scope_spans in resource_spans.get("scopeSpans", []):
+                                for span in scope_spans.get("spans", []):
+                                    attributes = {
+                                        attribute["key"]: attribute["value"] for attribute in span.get("attributes", [])
+                                    }
+                                    if attributes.get("openinference.span.kind", {}).get("stringValue") != "LLM":
+                                        continue
+                                    n_input += token_count(attributes, "llm.token_count.prompt")
+                                    n_output += token_count(attributes, "llm.token_count.completion")
+                                    n_cache += token_count(
+                                        attributes,
+                                        "llm.token_count.prompt_details.cache_read",
+                                    )
+                    except (AttributeError, KeyError, TypeError, ValueError, json.JSONDecodeError) as exc:
+                        raise ValueError(f"Invalid trace data in {path}:{line_number}: {exc}") from exc
+        return {"n_input_tokens": n_input, "n_output_tokens": n_output, "n_cache_tokens": n_cache}
+
+    async def run(
+        self,
+        instruction: str,
+        environment: BaseEnvironment,
+        context: AgentContext,
+    ) -> None:
+        env = {name: value for name in MODEL_CREDENTIAL_VARS if (value := os.environ.get(name))}
+        if self.model_name:
+            env["NEMO_AGENT_MODEL"] = self.model_name
+        proc = await environment.exec(
+            f"cd /app && uv run --frozen python main.py --prompt {shlex.quote(instruction.strip())}",
+            env=env,
+        )
+        # download traces from container to parse token counts on the host
+        _tmp = tempfile.mkdtemp(prefix="agent_traces_")
+        metrics_error = None
+        try:
+            await environment.download_dir(TRACES_DIR, _tmp)
+            metrics = self._parse_trace_metrics(_tmp)
+            context.n_input_tokens = metrics["n_input_tokens"]
+            context.n_output_tokens = metrics["n_output_tokens"]
+            context.n_cache_tokens = metrics["n_cache_tokens"]
+        except (FileNotFoundError, OSError, ValueError) as exc:
+            metrics_error = f"Trace metrics unavailable: {type(exc).__name__}: {exc}"
+            logger.warning(metrics_error)
+        finally:
+            shutil.rmtree(_tmp, ignore_errors=True)
+        # copy the traces directory to the artifacts directory (no-op if absent)
+        await environment.exec(f"cp -r {TRACES_DIR} {COLLECTED_ARTIFACTS_DIR}/traces 2>/dev/null || true")
+        # recursive so subdirs like artifacts/traces/ survive if the agent wrote there
+        await environment.exec(f"sh -c 'cp -r {ARTIFACTS_DIR}/* {COLLECTED_ARTIFACTS_DIR}/ 2>/dev/null || true'")
+
+        context.metadata = {
+            "stdout": proc.stdout,
+            "stderr": proc.stderr,
+            "returncode": proc.return_code,
+            "metrics_error": metrics_error,
+        }
+        if proc.return_code != 0:
+            raise RuntimeError(f"Agent process failed with exit code {proc.return_code}: {proc.stderr or proc.stdout}")
diff --git a/plugins/nemo-experimentalist/examples/tau3-nooa-agent/main.py b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/main.py
new file mode 100644
index 0000000000..86ee6813b8
--- /dev/null
+++ b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/main.py
@@ -0,0 +1,15 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import argparse
+import asyncio
+
+from agent import Codeact
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--prompt", type=str, required=True)
+    args = parser.parse_args()
+
+    agent = Codeact()
+    asyncio.run(agent.solve(args.prompt))
diff --git a/plugins/nemo-experimentalist/examples/tau3-nooa-agent/pyproject.toml b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/pyproject.toml
new file mode 100644
index 0000000000..a283668c72
--- /dev/null
+++ b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/pyproject.toml
@@ -0,0 +1,18 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+[project]
+name = "nemo-tau3-oo-agent"
+version = "0.1.0"
+description = "NOOA agent under test for tau3-bench"
+readme = "README.md"
+requires-python = ">=3.12,<3.14"
+dependencies = [
+    "mcp==1.25.0",
+    "nooa[tracing]",
+    "opentelemetry-exporter-otlp-proto-http",
+    "orjson==3.11.9",
+]
+[tool.uv.sources]
+# Keep in step with the workspace root pin.
+nooa = { git = "https://github.com/NVIDIA-NeMo/labs-OO-Agents.git", rev = "bea4614a0e2a6cf88f76225466159af883da80a0" }
diff --git a/plugins/nemo-experimentalist/examples/tau3-nooa-agent/uv.lock b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/uv.lock
new file mode 100644
index 0000000000..00440ced9c
--- /dev/null
+++ b/plugins/nemo-experimentalist/examples/tau3-nooa-agent/uv.lock
@@ -0,0 +1,1572 @@
+version = 1
+revision = 3
+requires-python = ">=3.12, <3.14"
+
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.7.1"
+source = { registry = "https://pypi.org/simple" }
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+]
+
+[[package]]
+name = "aiohttp"
+version = "3.14.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
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+    { name = "aiosignal" },
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+version = "4.1.0"
+source = { registry = "https://pypi.org/simple" }
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+wheels = [
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diff --git a/plugins/nemo-experimentalist/framework-skills/nooa/SKILL.md b/plugins/nemo-experimentalist/framework-skills/nooa/SKILL.md
index 408f9cb421..04ce676323 100644
--- a/plugins/nemo-experimentalist/framework-skills/nooa/SKILL.md
+++ b/plugins/nemo-experimentalist/framework-skills/nooa/SKILL.md
@@ -1,10 +1,10 @@
 ---
 name: nooa
 description: Build, modify, debug, or optimize agents using NVIDIA-labs OO Agents (NOOA). Use for nooa.Agent subclasses, ellipsis generation methods, CodeAct or Predict strategies, ShellTools, Skill/TextSkill, context and persistence, MCP, tracing, middleware, channels, or trace analysis.
-compatibility: Python >= 3.12,<3.14; uv; nooa v0.0.6
+compatibility: Python >= 3.12,<3.14; uv; nooa at the revision pinned in pyproject.toml
 metadata:
   upstream: https://github.com/NVIDIA-NeMo/labs-OO-Agents
-  revision: v0.0.6
+  revision: bea4614a0e2a6cf88f76225466159af883da80a0
 ---
 <!-- SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. -->
 <!-- SPDX-License-Identifier: Apache-2.0 -->
@@ -13,9 +13,9 @@ metadata:
 
 Use the `nooa` package and namespace pinned in this repository.
 
-For detailed framework guidance, consult the immutable upstream `v0.0.6`
-skills:
-https://github.com/NVIDIA-NeMo/labs-OO-Agents/tree/v0.0.6/skills
+For detailed framework guidance, consult the skills at the immutable upstream
+revision this repository pins:
+https://github.com/NVIDIA-NeMo/labs-OO-Agents/tree/bea4614a0e2a6cf88f76225466159af883da80a0/skills
 
 Before changing framework behavior, inspect the pinned implementation or the
 matching upstream skill instead of guessing. In Optimizer:
@@ -23,8 +23,8 @@ matching upstream skill instead of guessing. In Optimizer:
 - Call `super().__init__()` before attaching tools or skills.
 - Use `GuardedShellTools` where workspace access must remain restricted.
 - Hide internal skill registries with `spec(self, "skills", hidden=True)`.
-- Keep the explicit `orjson==3.11.9` workaround required by the v0.0.6
-  LiteLLM tool-call path.
+- Keep the explicit `orjson==3.11.9` workaround required by nooa's LiteLLM
+  tool-call path.
 
 ## Verification
 
diff --git a/plugins/nemo-experimentalist/tests/test_experimentalist_benchmark.py b/plugins/nemo-experimentalist/tests/test_experimentalist_benchmark.py
index caab7cc8a6..fd6bbc7611 100644
--- a/plugins/nemo-experimentalist/tests/test_experimentalist_benchmark.py
+++ b/plugins/nemo-experimentalist/tests/test_experimentalist_benchmark.py
@@ -3,6 +3,7 @@
 
 import importlib.util
 import json
+import os
 from pathlib import Path
 from types import ModuleType
 
@@ -47,7 +48,10 @@ def test_shipped_suite_covers_canonical_count_and_fast_subset() -> None:
     assert "install-windows-3-11" not in canonical_ids
 
 
-@pytest.mark.parametrize("name", ["smoke.yaml", "quality.yaml"])
+@pytest.mark.parametrize(
+    "name",
+    ["terminal-bench-smoke.yaml", "terminal-bench-quality.yaml", "tau3-smoke.yaml", "tau3-quality.yaml"],
+)
 def test_shipped_benchmark_configs_use_current_contracts(name: str) -> None:
     runner = _load_runner()
 
@@ -57,6 +61,119 @@ def test_shipped_benchmark_configs_use_current_contracts(name: str) -> None:
     assert config.optimizer.eval_author.max_validation_repair_attempts >= 0
 
 
+def test_task_id_prefix_scopes_canonical_set_to_domain() -> None:
+    runner = _load_runner()
+    suite = runner.SuiteSpec.model_validate(
+        {
+            "schema_version": 1,
+            "dataset": {
+                "name": "sierra-research/tau3-bench",
+                "ref": "1",
+                "resolved_ref": "sha256:abc",
+                "registry_url": "https://hub.harborframework.com",
+                "source_url": "https://hub.harborframework.com/datasets/sierra-research/tau3-bench",
+                "expected_task_count": 2,
+                "task_id_prefix": "pkg__banking-",
+            },
+            # Partition entries are names inside task_id_prefix, not whole IDs.
+            "partitions": {
+                "source": {"commit": "deadbeef", "note": "IDs only."},
+                "quality": {"train": ["1"], "validation": ["2"], "test": ["3"]},
+                "fast": {"train": ["1"], "validation": ["2"], "test": ["3"]},
+            },
+            "workspace": "tau3-banking",
+            "framework_skills": ["nooa"],
+        }
+    )
+
+    assert suite.partitions.quality.train == ["pkg__banking-1"]
+
+    # Package holds two domains; only the banking three belong to this suite.
+    package_ids = {
+        "pkg__banking-1",
+        "pkg__banking-2",
+        "pkg__banking-3",
+        "pkg__retail-1",
+        "pkg__retail-2",
+    }
+
+    with pytest.raises(ValueError, match="expected 2"):
+        runner.validate_canonical_suite(suite, canonical_task_ids=package_ids, resolved_ref="sha256:abc")
+
+    suite.dataset.expected_task_count = 3
+    scoped = runner.validate_canonical_suite(suite, canonical_task_ids=package_ids, resolved_ref="sha256:abc")
+
+    assert scoped == {"pkg__banking-1", "pkg__banking-2", "pkg__banking-3"}
+
+    # A prefix matching nothing is a manifest bug, not an empty suite.
+    suite.dataset.task_id_prefix = "nope-"
+    with pytest.raises(ValueError, match="task_id_prefix"):
+        runner.validate_canonical_suite(suite, canonical_task_ids=package_ids, resolved_ref="sha256:abc")
+
+
+def test_suite_resolves_framework_skills_dirs_and_rejects_unknown_ones() -> None:
+    runner = _load_runner()
+    suite = runner.load_suite(BENCHMARK_ROOT / "suites" / "terminal-bench-2.1.yaml")
+
+    assert suite.workspace == "canonical-terminal-bench-2-1"
+    assert suite.framework_skills == ["langchain-framework"]
+    assert suite.framework_skills_dirs(PLUGIN_ROOT) == [PLUGIN_ROOT / "framework-skills" / "langchain-framework"]
+
+    suite.framework_skills = ["does-not-exist"]
+    with pytest.raises(ValueError, match="does-not-exist"):
+        suite.framework_skills_dirs(PLUGIN_ROOT)
+
+
+def test_user_simulator_exports_task_env_credentials(monkeypatch: pytest.MonkeyPatch) -> None:
+    runner = _load_runner()
+    task_env_names = ("OPENAI_API_KEY", "OPENAI_BASE_URL", "TAU2_USER_MODEL", "TAU2_NL_ASSERTIONS_MODEL")
+
+    def configure(
+        api_base: str | None,
+        user_simulator: str | None,
+        ambient: dict[str, str] | None = None,
+    ) -> dict[str, str]:
+        """Run ``_configure_models`` against a throwaway environ and return what it wrote."""
+        environ = {"INFERENCE_API_KEY": "key-123", **(ambient or {})}
+        if api_base is not None:
+            environ["INFERENCE_API_BASE"] = api_base
+        monkeypatch.setattr(os, "environ", environ)
+        runner._configure_models(
+            runner.ModelSpec(
+                aut="a",
+                experimentalist_smart="b",
+                experimentalist_mid="c",
+                experimentalist_fast="d",
+                user_simulator=user_simulator,
+            )
+        )
+        return environ
+
+    # Ambient values are seeded to prove the config wins over the developer's shell: a
+    # personal OPENAI_API_KEY paired with the gateway base URL would 401, and a stale
+    # TAU2_USER_MODEL would silently disagree with the NL-assertion judge.
+    exported = configure(
+        "https://inference-api.nvidia.com",
+        "openai/openai/openai/gpt-5-mini",
+        ambient={"OPENAI_API_KEY": "sk-personal", "TAU2_USER_MODEL": "gpt-4o-mini"},
+    )
+
+    assert exported["OPENAI_API_KEY"] == "key-123"
+    # litellm inside the sidecar needs the /v1 suffix, which INFERENCE_API_BASE lacks.
+    assert exported["OPENAI_BASE_URL"] == "https://inference-api.nvidia.com/v1"
+    assert exported["TAU2_USER_MODEL"] == "openai/openai/openai/gpt-5-mini"
+    assert exported["TAU2_NL_ASSERTIONS_MODEL"] == "openai/openai/openai/gpt-5-mini"
+
+    # A base already carrying /v1, and one with a trailing slash, both normalize to a
+    # single suffix; an unset base falls back to the default, which already has one.
+    for api_base in ("https://inference-api.nvidia.com/v1/", "https://inference-api.nvidia.com/", None):
+        assert configure(api_base, "m")["OPENAI_BASE_URL"] == "https://inference-api.nvidia.com/v1"
+
+    # Suites without a user simulator (Terminal Bench) must not have these set for them.
+    without_simulator = configure("https://inference-api.nvidia.com", None)
+    assert [name for name in task_env_names if name in without_simulator] == []
+
+
 def test_suite_validation_rejects_changed_dataset_revision() -> None:
     runner = _load_runner()
     suite = runner.load_suite(BENCHMARK_ROOT / "suites" / "terminal-bench-2.1.yaml")
diff --git a/pyproject.toml b/pyproject.toml
index 99cd6f423a..bed48200a6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -366,8 +366,10 @@ nmp-build-tools = { workspace = true }
 nemo-platform-plugin = { workspace = true }
 nemo-insights-plugin = { workspace = true }
 nemo-experimentalist-plugin = { workspace = true }
-# Not published to PyPI yet; pinned to an immutable public tag.
-nooa = { git = "https://github.com/NVIDIA-NeMo/labs-OO-Agents.git", tag = "v0.0.6" }
+# Not published to PyPI yet, so this pins an immutable public commit. It is a commit
+# rather than a tag because the MCP transport-timeout fix landed after v0.0.6; move
+# back to a tag once one ships that contains it.
+nooa = { git = "https://github.com/NVIDIA-NeMo/labs-OO-Agents.git", rev = "bea4614a0e2a6cf88f76225466159af883da80a0" }
 
 nemo-evaluator-plugin = { workspace = true }
 nemo-guardrails-plugin = { workspace = true }
@@ -618,8 +620,8 @@ exclude = [
   # root `ty` until that cleanup lands in a focused follow-up.
   "plugins/nemo-switchyard/",
 
-  # Standalone Terminal-Bench agent-under-test: resolved from its own lockfile inside
-  # the benchmark's task containers, so its imports are absent from the workspace env.
+  # Standalone agents-under-test: each resolves from its own lockfile inside the
+  # benchmark's task containers, so its imports are absent from the workspace env.
   "plugins/nemo-experimentalist/examples/",
 
   "docs/",
diff --git a/uv.lock b/uv.lock
index ff076b0d3f..69f2198569 100644
--- a/uv.lock
+++ b/uv.lock
@@ -4157,7 +4157,7 @@ requires-dist = [
     { name = "nemo-insights-plugin", editable = "plugins/nemo-insights" },
     { name = "nemo-platform", editable = "packages/nemo_platform" },
     { name = "nemo-platform-plugin", editable = "packages/nemo_platform_plugin" },
-    { name = "nooa", git = "https://github.com/NVIDIA-NeMo/labs-OO-Agents.git?tag=v0.0.6" },
+    { name = "nooa", git = "https://github.com/NVIDIA-NeMo/labs-OO-Agents.git?rev=bea4614a0e2a6cf88f76225466159af883da80a0" },
     { name = "opentelemetry-proto", specifier = ">=1.42.1" },
     { name = "protobuf", specifier = ">=6.0.0" },
     { name = "pydantic", specifier = ">=2" },
@@ -7507,8 +7507,8 @@ wheels = [
 
 [[package]]
 name = "nooa"
-version = "0.0.6"
-source = { git = "https://github.com/NVIDIA-NeMo/labs-OO-Agents.git?tag=v0.0.6#be0aad9db6cbce9b6a62ff08e3680284af091d6f" }
+version = "0.0.7.dev46"
+source = { git = "https://github.com/NVIDIA-NeMo/labs-OO-Agents.git?rev=bea4614a0e2a6cf88f76225466159af883da80a0#bea4614a0e2a6cf88f76225466159af883da80a0" }
 dependencies = [
     { name = "httpx", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
     { name = "litellm", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },