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ptorsten

humaans-mcp

by ptorsten

get_compensation

Retrieve a single compensation record by its ID. Access employee compensation details from the Humaans HRIS.

Instructions

Retrieve a single compensation record by id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compensation_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The get_compensation tool implementation: an async function decorated with @mcp.tool() that takes a compensation_id string and delegates to client().get() on the /compensations/{compensation_id} endpoint.
    @mcp.tool()
    async def get_compensation(compensation_id: str) -> dict[str, Any]:
        """Retrieve a single compensation record by id."""
        return await client().get(f"/compensations/{compensation_id}")
  • The tool is registered via the @mcp.tool() decorator on line 305, where mcp = FastMCP('humaans') is defined at line 7.
    @mcp.tool()
  • The client() helper function that lazily instantiates and returns a HumaansClient singleton, used by get_compensation to make the API call.
    def client() -> HumaansClient:
        global _client
        if _client is None:
            _client = HumaansClient()
        return _client
  • The HumaansClient.get() method used by get_compensation to perform the actual HTTP GET request to the Humaans API.
    async def get(self, path: str, params: dict[str, Any] | None = None) -> Any:
        clean = {k: v for k, v in (params or {}).items() if v is not None}
        resp = await self._client.get(path, params=clean)
        if resp.status_code >= 400:
            try:
                body = resp.json()
            except Exception:
                body = resp.text
            raise HumaansError(resp.status_code, path, body)
        return resp.json()
Behavior2/5

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

No annotations are present, so the description must cover behavioral traits. It only states 'retrieve', implying read-only, but provides no details on side effects, authorization, or limitations.

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

Conciseness5/5

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

The description is a single, concise sentence with no unnecessary words, front-loading the purpose.

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

Completeness4/5

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

Given the tool's simplicity and presence of an output schema, the description is mostly complete. It could benefit from noting that the ID is required, but that is already in the schema.

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

Parameters2/5

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

Schema description coverage is 0%, so the description should compensate. It mentions 'by id' but adds no further meaning (e.g., format, constraints) beyond the schema's type 'string'.

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 it retrieves a single compensation record by ID, using a specific verb and resource. This distinguishes it from list_compensations, which retrieves multiple records.

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

Usage Guidelines3/5

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

Usage is implied by the context of sibling tools (e.g., list_compensations for querying multiple), but no explicit guidance on when to use this tool versus alternatives is provided.

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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