rapids-bot · Oct 7, 2026 · Oct 7, 2026 · Oct 7, 2026 · Oct 7, 2026 · Oct 7, 2026
@@ -10,6 +10,8 @@ adapters in Harbor tasks. Harbor options select the model, harness, skills, MCP
 servers, tool policy, and telemetry; `FabricAgent` translates them into one
 typed `FabricConfig` for the task run.
 
+Harbor's `skills_dir` is a task-side collection containing `<skill_name>/SKILL.md` directories. The task runner expands its immediate entries into individual NeMo Fabric skill paths in name order, preserving explicit `config.skills.paths` and avoiding duplicate paths. An empty collection adds no skills. Missing collections and entries without a regular `SKILL.md` file fail before harness execution; skill contents are still validated by the selected adapter. Collection paths are resolved inside the task environment, relative to `fabric_config_base_dir` when not absolute, never through the host filesystem. Use matching NeMo Fabric versions on the host and in the task environment for this transport contract.
+
 Refer to the [Harbor example](../../../../../../../examples/harbor/README.md)
 for runnable SWE-Bench commands, configuration variations, reward checks, and
 Relay artifacts.

@@ -512,6 +512,7 @@ def _build_spec(self, instruction: str) -> FabricRunPayload:
             return FabricRunPayload(
                 config=config,
                 config_base_dir=self._environment_config_base_dir,
+                skills_dir=self.skills_dir,
                 request=self._build_request(instruction),
                 environment_env_names=tuple(self.fabric_environment_env),
             )
@@ -531,7 +532,6 @@ def _build_config(self) -> FabricConfig:
                 enabled_tools=self.fabric_enabled_tools,
                 telemetry=self.fabric_telemetry,
                 model_name=self.model_name,
-                skills_dir=self.skills_dir,
                 mcp_servers=tuple(
                     HarborMcpServer.model_validate(server.model_dump(mode="python"))
                     for server in self.mcp_servers
@@ -623,7 +623,6 @@ def build_harbor_config(
     enabled_tools: list[str] | None = None,
     telemetry: Literal["none", "relay"] = "none",
     model_name: str | None = None,
-    skills_dir: str | Path | None = None,
     mcp_servers: tuple[HarborMcpServer, ...] = (),
     discovery_paths: tuple[str | Path, ...] = (),
 ) -> FabricConfig:
@@ -713,8 +712,6 @@ def build_harbor_config(
                 url=cast(str, server.url),
                 exposure="harness_native",
             )
-    if skills_dir is not None:
-        config.add_skill_path(skills_dir)
     if telemetry == "relay":
         relay_output = f"{artifact_root}/relay"
         config.enable_relay(

@@ -49,6 +49,7 @@ class FabricRunPayload(BaseModel):
     config: FabricConfig
     config_base_dir: PurePosixPath
     logs_dir: PurePosixPath = PurePosixPath("/logs/agent")
+    skills_dir: PurePosixPath | None = None
     request: RunRequest
     environment_env_names: tuple[str, ...] = ()
 

@@ -12,6 +12,7 @@
 from pathlib import Path
 
 from nemo_fabric import Fabric
+from nemo_fabric import FabricConfigError
 from nemo_fabric import FabricError
 from nemo_fabric import RunResult
 from nemo_fabric.integrations.harbor.models import FabricRunPayload
@@ -26,6 +27,41 @@ async def run(payload: FabricRunPayload) -> RunResult:
         if name not in os.environ:
             raise ValueError(f"Harbor runner environment variable {name} is not set")
         config.environment.env[name] = os.environ[name]
+    if payload.skills_dir is not None:
+        base_dir = Path(payload.config_base_dir).resolve()
+        root = Path(payload.skills_dir)
+        if not root.is_absolute():
+            root = base_dir / root
+        if not root.is_dir():
+            raise FabricConfigError(
+                f"Harbor skills collection must be an existing task-side directory: {root}",
+                stage="configuration",
+                code="harbor_skills_invalid",
+            )
+        skills = sorted(root.iterdir())
+        for skill in skills:
+            skill_file = skill / "SKILL.md"
+            if (
+                not skill.is_dir()
+                or skill_file.is_symlink()
+                or not skill_file.is_file()
+            ):
+                raise FabricConfigError(
+                    "Harbor skills collection entries must be directories "
+                    f"containing a regular SKILL.md file: {skill}",
+                    stage="configuration",
+                    code="harbor_skills_invalid",
+                )
+        existing_paths = (
+            {(base_dir / path).resolve() for path in config.skills.paths}
+            if config.skills is not None
+            else set()
+        )
+        for skill in skills:
+            resolved = skill.resolve()
+            if resolved not in existing_paths:
+                config.add_skill_path(skill)
+                existing_paths.add(resolved)
     result = await Fabric().run(
         config,
         base_dir=payload.config_base_dir,

@@ -52,15 +52,14 @@ def load_codex_adapter():
     return adapter
 
 
-def test_harbor_builder_constructs_complete_config_from_harbor_inputs(tmp_path):
+def test_harbor_builder_constructs_complete_config_from_harbor_inputs():
     from nemo_fabric.integrations.harbor.fabric_agent import build_harbor_config
     from nemo_fabric.integrations.harbor.models import HarborMcpServer
 
     config = build_harbor_config(
         adapter_id="demo.fabric.smoke",
         workspace="/testbed",
         model_name="openai/gpt-5.4",
-        skills_dir=tmp_path / "skills",
         mcp_servers=(
             HarborMcpServer(
                 name="remote",
@@ -85,8 +84,7 @@ def test_harbor_builder_constructs_complete_config_from_harbor_inputs(tmp_path):
     assert config.mcp.servers["local"].url == "mcp-server"
     assert config.mcp.servers["local"].args == ["--stdio"]
     assert "args" not in config.mcp.servers["local"].extra_fields
-    assert config.skills is not None
-    assert config.skills.paths == [str(tmp_path / "skills")]
+    assert config.skills is None
     assert (
         json.loads(json.dumps(config.to_mapping()))["metadata"]["name"]
         == "harbor-smoke"
@@ -135,6 +133,7 @@ def test_harbor_transport_models_validate_mcp_targets():
         "config",
         "config_base_dir",
         "logs_dir",
+        "skills_dir",
         "request",
         "environment_env_names",
     }
@@ -552,7 +551,6 @@ def test_swebench_matrix_translates_harbor_inputs_to_typed_config(tmp_path: Path
         workspace="/testbed",
         telemetry="relay",
         model_name="nvidia/nemotron-3-nano-omni-30b-a3b-reasoning",
-        skills_dir="/harbor/skills",
         mcp_servers=tuple(
             HarborMcpServer.model_validate(server.model_dump(mode="python"))
             for server in load_mcp_servers(SWEBENCH_MCP_CONFIG)
@@ -586,8 +584,7 @@ def test_swebench_matrix_translates_harbor_inputs_to_typed_config(tmp_path: Path
     assert (
         relay.models["default"].model == "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning"
     )
-    assert relay.skills is not None
-    assert relay.skills.paths == ["/harbor/skills"]
+    assert relay.skills is None
     assert relay.mcp is not None
     assert set(relay.mcp.servers) == {"fabric-repo-inspector"}
     assert relay.mcp.servers["fabric-repo-inspector"].args == [