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 returns itemized disbursements with specific fields (recipient, amount, date), mentions filtering capability via recipient_name, implies pagination through the per_page parameter, and provides real-world examples of what the output looks like. The only minor gap is it doesn't explicitly mention rate limits or authentication requirements.

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 with the core purpose. Every sentence adds value: purpose statement, investigative context, concrete example, workflow guidance, and practical tips. While slightly longer than minimal, all content is relevant and helpful for tool selection and usage. The only minor improvement would be slightly tighter formatting of the example section.

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?

For a tool with 4 parameters, 100% schema coverage, but no output schema or annotations, the description provides excellent context. It explains what the tool returns, gives concrete output examples, provides workflow integration with sibling tools, and offers practical usage advice. The only gap is the lack of explicit output format description, but the examples effectively illustrate what to expect.

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?

With 100% schema description coverage, the baseline is 3. The description adds significant value beyond the schema: it provides concrete examples of parameter values (e.g., committee_id='C00004275', cycle=2018, recipient_name='Crapo'), explains the relationship between parameters (recipient_name filters results), and gives context about parameter significance (cycle must be election year ±1). It also provides common PAC IDs that aren't in the schema.

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 clearly states the tool's purpose: 'Get itemized disbursements from a PAC or committee' with specific details about what it shows (which candidates/committees received money, how much, when). It distinguishes itself from siblings by being the 'KEY tool for conflict-of-interest investigations' and mentions a specific sibling tool (fec_search_committees) in the workflow.

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 usage guidance: it states when to use this tool ('for conflict-of-interest investigations'), provides a complete workflow with step-by-step instructions mentioning sibling tools, gives advice about trying multiple cycles, and includes concrete examples with specific parameter values. It even provides common PAC IDs for immediate use.

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