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. It describes what the tool returns (project details like number, title, PI, etc.) and implies it's a search/read operation, but doesn't disclose important behavioral traits like pagination behavior (though the schema has limit/offset), rate limits, authentication requirements, or error conditions. The description adds some context but leaves significant 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 perfectly structured: first sentence states purpose and searchable fields, second sentence specifies return values, third sentence provides usage examples. Every sentence earns its place with zero wasted words, and the most important information (what it searches) is front-loaded.

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 complex tool with 17 parameters and no output schema, the description provides good purpose and usage context but lacks important details about behavioral characteristics (pagination, rate limits, etc.) and doesn't explain the return format beyond listing fields. With no annotations and no output schema, the description should do more to compensate for these gaps.

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?

Schema description coverage is 100%, so the schema already documents all 17 parameters thoroughly. The description mentions searchable fields that map to parameters (text, disease area, investigator, etc.) but doesn't add significant semantic meaning beyond what's in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

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: 'Search NIH-funded research projects' with a comprehensive list of searchable fields (text, disease area, investigator, institution, etc.). It clearly distinguishes this from sibling tools by focusing specifically on NIH research grants, unlike the many other government data tools in the sibling list.

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 clear usage context with examples: 'Use to find research grants for any disease, track institutional funding, or identify PIs.' This gives practical scenarios when to use the tool. However, it doesn't explicitly state when NOT to use it or name specific alternative tools for similar data.

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