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ptorsten

humaans-mcp

by ptorsten

list_custom_fields

List all custom fields configured in your Humaans account to review available data points.

Instructions

List all configured custom fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The tool handler function that executes the 'list_custom_fields' logic. It is decorated with @mcp.tool(), takes no parameters, and calls the Humaans API at '/custom-fields' with a limit of 250.
    @mcp.tool()
    async def list_custom_fields() -> Any:
        """List all configured custom fields."""
        return await client().list_page("/custom-fields", limit=250)
  • The tool is registered via the @mcp.tool() decorator on the async function. The FastMCP instance 'mcp' (created at line 7) registers this function as an MCP tool named 'list_custom_fields'.
    @mcp.tool()
  • The client().list_page() helper method called by the handler. It constructs query parameters (filters, $limit, $skip) and makes an HTTP GET request to the Humaans API.
    async def list_page(
        self,
        path: str,
        filters: dict[str, Any] | None = None,
        limit: int = 100,
        skip: int = 0,
    ) -> Any:
        params = dict(filters or {})
        params["$limit"] = limit
        params["$skip"] = skip
        return await self.get(path, params)
Behavior3/5

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

Annotations are absent, so the description carries the full burden. It implies a read operation ('list') but does not disclose any behavioral traits such as permissions, rate limits, or pagination. A 3 is adequate for a simple, safe operation but lacks depth.

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, efficient sentence with no waste. It is front-loaded and every word serves a 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 zero parameters and no output schema, the description is mostly sufficient. However, it could briefly mention that the output is a list of custom field objects, adding a bit more context for an agent.

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

Parameters4/5

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

The input schema has zero parameters and is fully covered (100%). With no parameters, the description does not need to add param info; a baseline of 4 is appropriate as the description is not required to add more.

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 'List all configured custom fields' uses a specific verb ('list') and resource ('custom fields'), clearly distinguishing it from sibling tools like 'list_companies' and 'list_people'.

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 is provided on when to use this tool versus alternatives. With many list_* siblings, the description should clarify that this is for custom fields only, but it does not mention exclusions or context.

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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