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 full burden. It mentions the return data structure ('campaign numbers, affected components, consequences, and remedies'), which adds some behavioral context, but fails to disclose critical traits like whether this is a read-only operation, potential rate limits, authentication needs, error handling, or data freshness. For a search tool with zero annotation coverage, this 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 a single, well-structured sentence that efficiently conveys purpose, parameters, and return values without any wasted words. It is appropriately sized and front-loaded with essential information.

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's moderate complexity (3 required parameters, no output schema, no annotations), the description is partially complete. It covers purpose and return values but lacks behavioral transparency (e.g., safety, limits) and usage guidelines. The absence of an output schema means the description should ideally detail response structure more thoroughly, which it does only at a high level.

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 fully documents all three parameters (make, model, model_year) with examples. The description adds no additional parameter semantics beyond what the schema provides, such as format constraints or validation rules, meeting the baseline for high schema 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 specific action ('Search'), resource ('NHTSA vehicle recalls'), and filtering criteria ('by make, model, and model year'), distinguishing it from sibling tools like 'nhtsa_complaints' or 'nhtsa_safety_ratings' which handle different NHTSA data types. It provides a complete purpose statement without redundancy.

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 implies usage when searching for recalls by vehicle attributes, but provides no explicit guidance on when to use this tool versus alternatives (e.g., other NHTSA tools or general search tools). It lacks prerequisites, exclusions, or comparative context with siblings.

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