NVIDIA-NeMo · dmariali · Aug 4, 2026 · Aug 4, 2026 · Aug 4, 2026 · Aug 4, 2026
@@ -1,13 +1,13 @@
 ---
-name: nemo-agent-local
+name: nemo-studio-copilot
 created_timestamp: 2026-07-28T20:09:49Z
 author: Danielle Ali and Codex
 ---
 
-# Agent Spec: nemo-agent-local
+# Agent Spec: nemo-studio-copilot
 
 > This file is the durable contract for the local NeMo Platform assistant.
-> Keep it aligned with the implementation under `agents/nemo-agent-local/`.
+> Keep it aligned with the implementation under `agents/nemo-studio-copilot/`.
 
 ## Role
 
@@ -81,15 +81,15 @@ The mission is grounded in the current deployment proof of concept and its imple
 
 ## Evaluation Setup
 
-Unit coverage lives in `agents/nemo-agent-local/tests/test_nemo_agent.py`. Run it with:
+Unit coverage lives in `agents/nemo-studio-copilot/tests/test_nemo_studio_copilot.py`. Run it with:
 
 ```bash
-uv run --frozen pytest agents/nemo-agent-local/tests/test_nemo_agent.py -v
+uv run --frozen pytest agents/nemo-studio-copilot/tests/test_nemo_studio_copilot.py -v
 ```
 
-The NAT evaluation workflow is `agents/nemo-agent-local/src/nemo_agent/nemo-eval.yml`, with inputs in `nemo-eval-data.json`. It currently evaluates workspace creation, workspace listing, and model/provider listing with a tunable RAG judge weighted for coverage (0.5), correctness (0.3), and relevance (0.2). No formal aggregate pass threshold is defined.
+The NAT evaluation workflow is `agents/nemo-studio-copilot/src/nemo_studio_copilot/nemo-studio-copilot-eval.yml`, with inputs in `nemo-studio-copilot-eval-data.json`. It currently evaluates workspace creation, workspace listing, and model/provider listing with a tunable RAG judge weighted for coverage (0.5), correctness (0.3), and relevance (0.2). No formal aggregate pass threshold is defined.
 
-Manual Studio validation is documented in `agents/nemo-agent-local/tests/smoke_test.md`. Current coverage gaps include fileset listing, missing-workspace clarification, fast-path failure containment, destructive-action ambiguity, iteration limits, retry limits, cancellation, and end-to-end latency thresholds.
+Manual Studio validation is documented in `agents/nemo-studio-copilot/tests/smoke_test.md`. Current coverage gaps include fileset listing, missing-workspace clarification, fast-path failure containment, destructive-action ambiguity, iteration limits, retry limits, cancellation, and end-to-end latency thresholds.
 
 ## Change Scope
 

@@ -17,5 +17,5 @@ build/
 .venv/
 node_modules/
 tests/
-src/nemo_agent/nemo-eval.yml
-src/nemo_agent/nemo-eval-data.json
+src/nemo_studio_copilot/nemo-studio-copilot-eval.yml
+src/nemo_studio_copilot/nemo-studio-copilot-eval-data.json
@@ -41,19 +41,19 @@ RUN --mount=type=cache,id=uv_cache,target=/root/.cache/uv,sharing=locked \
     uv pip install . && \
     chmod -R a+rX /opt/uv /workspace/.venv
 
-LABEL org.opencontainers.image.title="builtin-nemo-agent" \
+LABEL org.opencontainers.image.title="nemo-studio-copilot" \
       org.opencontainers.image.version="0.1.0" \
       org.opencontainers.image.authors="NVIDIA" \
       org.opencontainers.image.created="2026-07-22T20:51:42.179931+00:00" \
-      org.opencontainers.image.description="Built-in NeMo Platform agent — a LangChain Deep Agent that uses the NeMo SDK to perform platform tasks." \
+      org.opencontainers.image.description="NeMo Copilot — a LangChain Deep Agent that uses the NeMo SDK to perform platform tasks." \
       org.opencontainers.image.revision="" \
       org.opencontainers.image.source="" \
       com.nemo.agent.id="790bd61b98d0" \
       com.nemo.agent.framework="nemo_agent_toolkit" \
       com.nemo.agent.nat-version="1.8.0" \
       com.nemo.agent.contract-version="0.0.0"
 
-ENV NAT_CONFIG_FILE=/workspace/src/nemo_agent/nemo-agent.yml
+ENV NAT_CONFIG_FILE=/workspace/src/nemo_studio_copilot/nemo-studio-copilot.yml
 
 ENV PATH="/workspace/.venv/bin:$PATH"
 

@@ -6,9 +6,9 @@ requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [project]
-name = "builtin-nemo-agent"
+name = "nemo-studio-copilot"
 version = "0.1.0"
-description = "Built-in NeMo Platform agent — a LangChain Deep Agent that uses the NeMo SDK to perform platform tasks."
+description = "NeMo Copilot — a LangChain Deep Agent that uses the NeMo SDK to perform platform tasks."
 requires-python = ">=3.11,<3.14"
 dependencies = [
     "nvidia-nat-core>=1.8.0,<1.9",
@@ -21,13 +21,13 @@ dependencies = [
 ]
 
 [project.entry-points."nat.components"]
-nemo_agents_nemo_agent = "nemo_agent.register"
-# Custom NAT workflow type that wraps the nemo-agent graph with permissive
-# input/output schemas. See src/nemo_agent/wrapper.py for the full rationale —
+nemo_studio_copilot = "nemo_studio_copilot.register"
+# Custom NAT workflow type that wraps the nemo-studio-copilot graph with permissive
+# input/output schemas. See src/nemo_studio_copilot/wrapper.py for the full rationale —
 # in short, NAT 1.6.0's stock `langgraph_wrapper` doesn't accept the
 # `{"input_message": ...}` shape that `nvidia-nat-eval` posts and crashes on
 # deep-agent state deltas that don't carry `messages`.
-nemo_agents_nemo_agent_wrapper = "nemo_agent.wrapper"
+nemo_studio_copilot_wrapper = "nemo_studio_copilot.wrapper"
 
 [tool.hatch.build.targets.wheel]
-packages = ["src/nemo_agent"]
+packages = ["src/nemo_studio_copilot"]
@@ -1,9 +1,9 @@
-# Eval config for the built-in nemo-agent.
+# Eval config for the built-in nemo-studio-copilot.
 #
-# Uses the custom `nemo_agent_wrapper` workflow type (defined in
-# src/nemo_agent/wrapper.py) so the same config works whether the agent runs
+# Uses the custom `nemo_studio_copilot_wrapper` workflow type (defined in
+# src/nemo_studio_copilot/wrapper.py) so the same config works whether the agent runs
 # inline (no --agent) or against the deployed agent's `/generate/full` endpoint
-# (--agent nemo-agent). The wrapper accepts both the `{"messages": [...]}`
+# (--agent nemo-studio-copilot). The wrapper accepts both the `{"messages": [...]}`
 # shape used by chat clients and the `{"input_message": "..."}` shape that
 # `nvidia-nat-eval`'s remote workflow client posts to `/generate/full`.
 #
@@ -13,13 +13,13 @@
 #
 # Run inline (in-process, no deployed agent needed):
 #   nemo agents evaluate run \
-#       --eval-config plugins/nemo-agents/builtin_agents/nemo-agent/src/nemo_agent/nemo-eval.yml \
+#       --eval-config agents/nemo-studio-copilot/src/nemo_studio_copilot/nemo-studio-copilot-eval.yml \
 #       --output ./eval-out
 #
-# Run against the deployed agent (requires `nemo agents deploy nemo-agent`):
+# Run against the deployed agent (requires `nemo agents deploy nemo-studio-copilot`):
 #   nemo agents evaluate run \
-#       --eval-config plugins/nemo-agents/builtin_agents/nemo-agent/src/nemo_agent/nemo-eval.yml \
-#       --agent nemo-agent \
+#       --eval-config agents/nemo-studio-copilot/src/nemo_studio_copilot/nemo-studio-copilot-eval.yml \
+#       --agent nemo-studio-copilot \
 #       --output ./eval-out
 
 llms:
@@ -47,7 +47,7 @@ llms:
   # only meaningful when something resolves it back to the upstream model.
   #
   # Caveat: the agent's tools (`nemo_api`, `check_status`) still call platform
-  # APIs via the Python SDK. The current `nemo-eval-data.json` exercises
+  # APIs via the Python SDK. The current `nemo-studio-copilot-eval-data.json` exercises
   # platform resources, including workspace and model/provider operations, so
   # bypassing the gateway is not an LLM-only smoke test. A fully self-contained
   # bypass run requires a separate pure-LLM dataset that does not invoke
@@ -67,16 +67,16 @@ llms:
   #     max_tokens: 1024
 
 workflow:
-  _type: nemo_agent_wrapper
+  _type: nemo_studio_copilot_wrapper
   description: NeMo Platform assistant using LangChain Deep Agents
 
 eval:
   general:
     max_concurrency: 1
-    output_dir: eval/nemo-agent
+    output_dir: eval/nemo-studio-copilot
     dataset:
       _type: json
-      file_path: nemo-eval-data.json
+      file_path: nemo-studio-copilot-eval-data.json
       structure:
         question_key: input_message
         answer_key: expected_output

@@ -18,5 +18,5 @@ llms:
     request_timeout: 120
 
 workflow:
-  _type: nemo_agent_wrapper
+  _type: nemo_studio_copilot_wrapper
   description: NeMo Platform assistant using LangChain Deep Agents
@@ -1,18 +1,17 @@
-# NeMo Platform Agent — NAT workflow configuration
+# NeMo Copilot — NAT workflow configuration
 #
 # A LangChain Deep Agent that uses the NeMo SDK to perform platform tasks.
 # Deliberately configured as the "expensive baseline" for the optimization
 # pipeline to compress.
 #
 # Deploy:
 #   uv pip install -e plugins/nemo-agents
-#   uv pip install -e plugins/nemo-agents/builtin_agents/nemo-agent
-#   nemo agents create --name nemo-agent \
-#     --agent-config plugins/nemo-agents/builtin_agents/nemo-agent/src/nemo_agent/nemo-agent.yml
-#   nemo agents deploy --agent nemo-agent
+#   nemo agents create --name nemo-studio-copilot \
+#     --agent-config agents/nemo-studio-copilot/src/nemo_studio_copilot/nemo-studio-copilot.yml
+#   nemo agents deploy --agent nemo-studio-copilot
 #
 # Invoke:
-#   nemo agents invoke --agent nemo-agent --input "Create a workspace called demo"
+#   nemo agents invoke --agent nemo-studio-copilot --input "Create a workspace called demo"
 
 llms:
   agent:
@@ -73,9 +72,9 @@ llms:
     # max_tokens: 49152
 
 workflow:
-  # Custom workflow type registered by `nemo-agents-nemo-agent`. Wraps the same
+  # Custom workflow type registered by `nemo_studio_copilot_wrapper`. Wraps the same
   # deep-agent graph as `langgraph_wrapper` would, but with input/output schemas
   # that survive both the eval client's `{"input_message": ...}` payload and the
-  # deep-agent's wider state shape. See src/nemo_agent/wrapper.py.
-  _type: nemo_agent_wrapper
+  # deep-agent's wider state shape. See src/nemo_studio_copilot/wrapper.py.
+  _type: nemo_studio_copilot_wrapper
   description: NeMo Platform assistant using LangChain Deep Agents
@@ -51,7 +51,7 @@
 SKILLS_DIR = Path(__file__).parent / "skills"
 DEFAULT_WORKSPACE = "default"
 DEFAULT_RECURSION_LIMIT = 24
-STUDIO_CALLBACK_PATH = "/studio/api/coding-agents/mcp/{session_id}"
+STUDIO_CALLBACK_PATH = "/studio/api/copilot/mcp/{session_id}"
 STUDIO_CALLBACK_TIMEOUT_SECONDS = 3600.0
 _READ_ONLY_SDK_ACTIONS = frozenset(
     {
@@ -80,14 +80,38 @@
 )
 _FAST_PATH_ANALYSIS = re.compile(r"\b(analy[sz]e|audit|compare|explain|investigate|why)\b", re.IGNORECASE)
 _DIRECT_LIST_RESOURCES = (
-    (re.compile(r"\bworkspaces?\b", re.IGNORECASE), "workspaces"),
-    (re.compile(r"\bmodels?\b", re.IGNORECASE), "models"),
+    # Match the requested resource before the contextual workspace qualifier.
+    # Provider prompts commonly include both "model" and "workspace", so the
+    # most specific resource must come first and workspace must come last.
     (re.compile(r"\bproviders?\b", re.IGNORECASE), "inference.providers"),
     (re.compile(r"\bfilesets?\b", re.IGNORECASE), "files.filesets"),
     (re.compile(r"\bdatasets?\b", re.IGNORECASE), "datasets"),
     (re.compile(r"\bbenchmarks?\b", re.IGNORECASE), "evaluation.benchmarks"),
     (re.compile(r"\bmetrics?\b", re.IGNORECASE), "evaluation.metrics"),
+    (re.compile(r"\bmodels?\b", re.IGNORECASE), "models"),
+    (re.compile(r"\bworkspaces?\b", re.IGNORECASE), "workspaces"),
 )
+_DIRECT_LIST_CONTEXT_TARGET = re.compile(
+    r"^\s*(?:list|show|what|which)\b.*?\b(?:"
+    r"(?P<providers>(?:model\s+)?providers?)|"
+    r"(?P<filesets>filesets?)|"
+    r"(?P<datasets>datasets?)|"
+    r"(?P<benchmarks>benchmarks?)|"
+    r"(?P<metrics>metrics?)|"
+    r"(?P<models>models?)|"
+    r"(?P<workspaces>workspaces?)"
+    r")\b",
+    re.IGNORECASE,
+)
+_DIRECT_LIST_CONTEXT_RESOURCES = {
+    "providers": "inference.providers",
+    "filesets": "files.filesets",
+    "datasets": "datasets",
+    "benchmarks": "evaluation.benchmarks",
+    "metrics": "evaluation.metrics",
+    "models": "models",
+    "workspaces": "workspaces",
+}
 
 _client: NeMoPlatform | None = None
 
@@ -108,6 +132,9 @@ def _direct_list_resource(messages: list[Any]) -> str | None:
         return None
     if _FAST_PATH_MUTATION.search(latest_user_text) or _FAST_PATH_ANALYSIS.search(latest_user_text):
         return None
+    context_target = _DIRECT_LIST_CONTEXT_TARGET.search(latest_user_text)
+    if context_target and context_target.lastgroup:
+        return _DIRECT_LIST_CONTEXT_RESOURCES[context_target.lastgroup]
     for pattern, resource_path in _DIRECT_LIST_RESOURCES:
         if pattern.search(latest_user_text):
             return resource_path
@@ -147,7 +174,7 @@ def _list_resource_names(resource_path: str) -> str:
         resource = _resolve_resource(_get_client(), resource_path)
         serialized = _serialize(_call_sdk_method(resource, "list"))
     except Exception as exc:
-        logger.exception("nemo-agent: direct list fast path failed for resource=%s", resource_path)
+        logger.exception("nemo-studio-copilot: direct list fast path failed for resource=%s", resource_path)
         return _direct_list_error(resource_path, exc)
 
     if isinstance(serialized, dict):
@@ -157,7 +184,7 @@ def _list_resource_names(resource_path: str) -> str:
     names = [item.get("name") for item in serialized if isinstance(item, dict) and isinstance(item.get("name"), str)]
     if not names:
         return f"No {resource_path.rsplit('.', maxsplit=1)[-1]} found in workspace '{_active_workspace()}'."
-    logger.info("nemo-agent: direct list fast path resource=%s count=%d", resource_path, len(names))
+    logger.info("nemo-studio-copilot: direct list fast path resource=%s count=%d", resource_path, len(names))
     return "\n".join(names)
 
 
@@ -169,7 +196,7 @@ def _delete_fileset(name: str) -> str:
         _call_sdk_method(resource, "delete", {"name": name})
         serialized = _serialize(_call_sdk_method(resource, "list"))
     except Exception as exc:
-        logger.exception("nemo-agent: direct fileset delete failed for name=%s", name)
+        logger.exception("nemo-studio-copilot: direct fileset delete failed for name=%s", name)
         if isinstance(exc, ValueError) and "workspace" in str(exc).lower():
             return f"Which workspace should I use to delete fileset '{name}'?"
         return f"I couldn't delete fileset '{name}' in workspace '{workspace}': {type(exc).__name__}: {exc}"
@@ -187,7 +214,7 @@ def _delete_fileset(name: str) -> str:
     if name in remaining_names:
         return f"I couldn't verify deletion: fileset '{name}' still exists in workspace '{workspace}'."
 
-    logger.info("nemo-agent: direct fileset delete name=%s workspace=%s", name, workspace)
+    logger.info("nemo-studio-copilot: direct fileset delete name=%s workspace=%s", name, workspace)
     return f"Deleted fileset '{name}' from workspace '{workspace}'."
 
 
@@ -663,7 +690,7 @@ def check_status(service: str, job_name: str) -> str:
 class _StreamSafeGraph:
     """Wraps a CompiledStateGraph with NAT-compatible incremental streaming.
 
-    The custom ``nemo_agent_wrapper`` accepts Deep Agent state deltas that do
+    The custom ``nemo_studio_copilot_wrapper`` accepts Deep Agent state deltas that do
     not contain ``messages``. Delegate to the graph's real ``astream`` so NAT
     can forward chunks as each graph step completes instead of buffering the
     entire run behind ``ainvoke``.
@@ -778,7 +805,9 @@ def _disable_nat_method_retries(model: Any) -> Any:
         object.__setattr__(model, name, types.MethodType(wrapped, model))
         disabled.append(name)
     if disabled:
-        logger.info("nemo-agent: disabled NAT automatic retry wrappers for model methods: %s", ", ".join(disabled))
+        logger.info(
+            "nemo-studio-copilot: disabled NAT automatic retry wrappers for model methods: %s", ", ".join(disabled)
+        )
     return model
 
 
@@ -829,7 +858,7 @@ def _build_backend() -> CompositeBackend:
     return CompositeBackend(default=StateBackend(), routes=routes)
 
 
-def create_nemo_agent(config=None):
+def create_nemo_studio_copilot(config=None):
     """Create the NeMo Platform Deep Agent.
 
     Args:
@@ -845,14 +874,14 @@ def create_nemo_agent(config=None):
     skills = [str(SKILLS_DIR)] if discovered else None
     if SKILLS_DIR.is_dir() and not discovered:
         logger.warning(
-            "nemo-agent: SKILLS_DIR=%s is configured but no spec-compliant "
+            "nemo-studio-copilot: SKILLS_DIR=%s is configured but no spec-compliant "
             "skills were discovered (each skill must be a subdirectory with "
             "a SKILL.md starting with '---' YAML frontmatter). Agent will "
             "run without playbook scaffolding.",
             SKILLS_DIR,
         )
     elif discovered:
-        logger.info("nemo-agent: loaded %d skills: %s", len(discovered), ", ".join(discovered))
+        logger.info("nemo-studio-copilot: loaded %d skills: %s", len(discovered), ", ".join(discovered))
     backend = _build_backend()
     graph = create_deep_agent(
         model=model,
@@ -864,10 +893,10 @@ def create_nemo_agent(config=None):
     return _StreamSafeGraph(graph)
 
 
-# Module-level graph factory. The active workflow type is `nemo_agent_wrapper`
-# (see ./wrapper.py), which calls ``create_nemo_agent`` directly. This alias is
+# Module-level graph factory. The active workflow type is `nemo_studio_copilot_wrapper`
+# (see ./wrapper.py), which calls ``create_nemo_studio_copilot`` directly. This alias is
 # kept so the graph can also be loaded via ``_type: langgraph_wrapper`` with
 # ``graph: .../register.py:agent`` for ad-hoc debugging — note that path will
-# hit the NAT 1.6.0 input/output schema bugs that ``nemo_agent_wrapper``
+# hit the NAT 1.6.0 input/output schema bugs that ``nemo_studio_copilot_wrapper``
 # exists to work around.
-agent = create_nemo_agent
+agent = create_nemo_studio_copilot
@@ -4,7 +4,7 @@ description: "Benchmark task execution contract: complete every numbered require
 ---
 # Benchmark execution contract
 
-This skill defines the execution requirements that every nemo-agent run under
+This skill defines the execution requirements that every nemo-studio-copilot run under
 `tests/agentic-use/` must satisfy so the canonical gate
 (`tests/agentic-use/passrate_token_policy_gate.py`) can score the run on
 verifier pass-rate and token totals. See