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testmo_get_automation_run

Retrieve details of an automation run by its ID, with options to include related entities.

Instructions

Get details of a specific automation run.

Args: automation_run_id: The automation run ID. expands: Related entities to include.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
automation_run_idYes
expandsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for testmo_get_automation_run tool. It calls the Testmo API GET /automation/runs/{automation_run_id} with optional expands parameter and returns the result.
    @mcp.tool()
    async def testmo_get_automation_run(
        automation_run_id: int,
        expands: list[str] | None = None,
    ) -> dict[str, Any]:
        """Get details of a specific automation run.
    
        Args:
            automation_run_id: The automation run ID.
            expands: Related entities to include.
        """
        params: dict[str, Any] = {}
        if expands:
            params["expands"] = ",".join(expands)
        result = await _request(
            "GET",
            f"/automation/runs/{automation_run_id}",
            params=params if params else None,
        )
        return result.get("result", result)
  • The function signature defines the input schema: automation_run_id (int, required) and expands (optional list of strings).
    async def testmo_get_automation_run(
        automation_run_id: int,
        expands: list[str] | None = None,
    ) -> dict[str, Any]:
  • The @mcp.tool() decorator registers this function as an MCP tool named testmo_get_automation_run.
    @mcp.tool()
  • testmo-mcp.py:17-17 (registration)
    The import of testmo.tools.automation in the entry point registers all tools from automation.py, including testmo_get_automation_run.
    import testmo.tools.automation  # noqa: F401
  • The _request helper used by testmo_get_automation_run to make HTTP requests to the Testmo API.
    async def _request(
        method: str,
        endpoint: str,
        data: dict[str, Any] | None = None,
        params: dict[str, Any] | None = None,
    ) -> dict[str, Any]:
        async with _get_client() as client:
            response = await client.request(
                method=method,
                url=endpoint,
                json=data,
                params=params,
            )
            if response.status_code == 204:
                return {"success": True}
            if response.status_code >= 400:
                try:
                    error_body = response.json()
                except Exception:
                    error_body = response.text
                raise RuntimeError(
                    f"Testmo API error {response.status_code}: "
                    f"{json.dumps(error_body) if isinstance(error_body, dict) else error_body}"
                )
            return response.json()
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description bears full burden. It only says 'Get details,' with no disclosure of read-only nature, side effects, or behavior. The word 'get' implies read-only but is not explicit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short and front-loaded, but it is too sparse, omitting critical details. It earns its place but doesn't add enough value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 2 parameters (one required), no schema descriptions, and no behavioral transparency, the description is incomplete. The presence of an output schema does not compensate for lacking usage guidance and parameter semantics.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. Description merely repeats parameter names from the schema without adding any meaning, format, or constraints beyond the schema's type and title.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get details of a specific automation run,' using a specific verb and resource, and distinguishes it from sibling tools like testmo_list_automation_runs which list runs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like testmo_list_automation_runs or testmo_get_automation_source. No context about prerequisites or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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