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get_person

Retrieve comprehensive team member details including contact information, role, activity timestamps, and custom metadata from Productive.io for specific person identification.

Instructions

Get detailed information about a specific team member/person.

Returns comprehensive person details including:

  • Full name, email, and contact information

  • Role, title, and organizational details

  • Activity timestamps (joined, last seen)

  • Custom fields and additional metadata

  • Avatar and profile information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
person_idYesThe unique Productive person identifier

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • server.py:548-562 (registration)
    MCP tool registration for 'get_person' with input schema (Annotated[int, Field]) and docstring description. Thin wrapper delegating to tools.get_person.
    @mcp.tool
    async def get_person(
        ctx: Context,
        person_id: Annotated[int, Field(description="The unique Productive person identifier")],
    ) -> Dict[str, Any]:
        """Get detailed information about a specific team member/person.
    
        Returns comprehensive person details including:
        - Full name, email, and contact information
        - Role, title, and organizational details
        - Activity timestamps (joined, last seen)
        - Custom fields and additional metadata
        - Avatar and profile information
        """
        return await tools.get_person(ctx, person_id)
  • Core handler implementation: calls client.get_person, applies filter_response, handles ProductiveAPIError and general exceptions with ctx logging.
    async def get_person(ctx: Context, person_id: int) -> ToolResult:
        """Fetch a single person/team member by ID.
    
        Developer notes:
        - Wraps client.get_person(person_id).
        - Applies utils.filter_response to sanitize output.
        - Returns detailed information about a specific team member.
        """
        try:
            await ctx.info(f"Fetching person with ID: {person_id}")
            result = await client.get_person(person_id)
            await ctx.info("Successfully retrieved person")
    
            filtered = filter_response(result)
    
            return filtered
    
        except ProductiveAPIError as e:
            await _handle_productive_api_error(ctx, e, f"person {person_id}")
        except Exception as e:
            await ctx.error(f"Unexpected error fetching person: {str(e)}")
            raise e
  • Client library helper: makes HTTP GET request to Productive API endpoint /people/{person_id}.
    async def get_person(self, person_id: int) -> Dict[str, Any]:
        """Get person by ID"""
        return await self._request("GET", f"/people/{str(person_id)}")
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what information is returned but does not cover critical behavioral aspects such as authentication requirements, rate limits, error handling, or whether the operation is read-only (implied by 'Get' but not stated). For a tool with no annotations, this is a significant gap.

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 well-structured and concise. It starts with a clear purpose statement, followed by a bulleted list of return details that efficiently communicates scope without unnecessary elaboration. Every sentence earns its place, and it is front-loaded with the core functionality.

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 complexity (simple read operation with one parameter), the presence of an output schema (which likely details return values), and high schema coverage, the description is reasonably complete. It outlines the information returned, which complements the output schema. However, it lacks behavioral context like authentication or error handling, which slightly reduces completeness.

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

Parameters3/5

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

The input schema has 100% description coverage, with 'person_id' clearly documented as 'The unique Productive person identifier.' The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. With high schema coverage, the baseline score of 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Get detailed information about a specific team member/person.' It specifies the verb ('Get') and resource ('team member/person'), but does not explicitly differentiate it from sibling tools like 'get_people' (which likely lists multiple people) or 'quick_search' (which might search across resources). The purpose is clear but lacks sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'get_people' (for listing people) or 'quick_search' (for broader searches), nor does it specify prerequisites or exclusions. Usage is implied by the purpose but without explicit 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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