US Government Open Data MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it performs parallel calls to three endpoints, returns a comprehensive set of data (party history, terms served, committee assignments, photo, website, legislative activity), and has a default bill limit of 20 with a maximum of 50. However, it does not mention potential rate limits, error handling, or authentication requirements, which are minor gaps.

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

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

The description is well-structured and front-loaded, starting with the core functionality. Each sentence adds value: the first explains what the tool does, the second provides usage alternatives, and the third suggests ideal research contexts. There is no redundant or unnecessary information, making it highly efficient and easy to parse.

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

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

Given the complexity of combining three endpoints and the lack of output schema, the description does a strong job of outlining what data is returned (bio/details, legislation, party history, etc.) and how to use it in context. However, it does not detail the exact structure of the output or potential limitations like pagination or data freshness, which are minor omissions in an otherwise comprehensive description.

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

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

The schema description coverage is 100%, so the baseline is 3. The description adds value by clarifying the bioguide_id parameter: it provides examples ('P000197' for Pelosi, 'M000355' for McConnell) and references congress_search_members to find it. For bill_limit, it reiterates the default (20) and maximum (50), which aligns with the schema but reinforces key constraints, earning a score above baseline.

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

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

The description explicitly states the tool's purpose: 'Get a COMPLETE member of Congress profile in ONE call' and specifies it 'combines bio/details, recent sponsored legislation, and recent cosponsored legislation (3 endpoints in parallel).' It clearly distinguishes this from sibling tools like congress_member_details and congress_member_bills by emphasizing the comprehensive, parallel nature of the data retrieval.

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

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

The description provides explicit guidance on when to use this tool: 'Use this instead of calling congress_member_details + congress_member_bills (sponsored) + congress_member_bills (cosponsored) individually.' It also suggests ideal contexts: 'Accountability research — cross-reference with FEC (fec_candidate_financials) for donors, lobbying_search for industry lobbying, and congress_house_votes / congress_senate_votes for voting record,' effectively positioning it within a workflow.

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