US Government Open Data MCP

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

No annotations are provided, so the description carries the full burden. It mentions 'Count fields' which hints at aggregation capabilities, but it doesn't disclose key behavioral traits like whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like. The description adds some context (e.g., search examples and count fields) but leaves significant gaps for a tool with no annotations.

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 appropriately sized and front-loaded, starting with the core purpose. The example searches and count fields note are useful additions, but the structure could be slightly improved by separating guidelines more clearly. Overall, it's efficient with minimal waste, though not perfectly optimized.

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 tool has no annotations, no output schema, and 2 parameters with full schema coverage, the description is moderately complete. It covers the purpose and provides usage examples, but it lacks details on behavioral aspects (e.g., response format, error handling) and doesn't fully compensate for the absence of structured data. For a search tool with no output schema, more context on what results look like would be beneficial.

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 both parameters ('search' and 'limit') thoroughly. The description adds example search queries (e.g., 'antibody_truth:"Positive"') and mentions 'Count fields,' which provides some semantic context beyond the schema's technical descriptions. However, this doesn't significantly enhance understanding beyond what the schema provides, meeting the baseline for high coverage.

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 searches for 'COVID-19 serology test evaluation results' and specifies it's about 'FDA's evaluation of antibody test performance (sensitivity/specificity).' This provides a specific verb ('Search') and resource ('COVID-19 serology test evaluation results'), but it doesn't explicitly distinguish this tool from other FDA-related tools in the sibling list (like fda_animal_events, fda_approved_drugs, etc.), which would require a 5.

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 example searches that imply usage contexts (e.g., filtering by positive samples or manufacturer), but it doesn't explicitly state when to use this tool versus alternatives. Given the many sibling tools, there's no guidance on when this specific FDA serology search is preferred over other FDA or health-related tools, so usage is only implied through examples.

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