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 of behavioral disclosure. It mentions the dataset size ('336K+ records') and includes example queries, but fails to describe critical behaviors such as pagination, rate limits, authentication requirements, error handling, or what the output looks like (since there's no output schema). For a search tool with no annotation coverage, this leaves significant gaps in understanding how the tool operates beyond basic query syntax.

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: it starts with the core purpose, then provides examples and additional context. Every sentence adds value—the first states the purpose and scale, the second offers usage context, and the examples and count field note are directly relevant. It avoids redundancy and is structured for quick comprehension, though it could be slightly more streamlined by integrating the count field note into the examples 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?

Given the complexity of a search tool with 2 parameters, no annotations, and no output schema, the description is incomplete. It covers the purpose and provides query examples but lacks essential details: it doesn't explain the output format, pagination, error conditions, or any limitations (e.g., rate limits). Without annotations or an output schema, the description should do more to guide the agent on what to expect from the tool's behavior and results, making it inadequate for full contextual understanding.

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 schema already documents both parameters ('search' and 'limit') thoroughly. The description adds value by providing concrete example queries (e.g., 'products.product_code:HQY') and mentioning 'Count fields: products.openfda.device_class', which clarifies the semantics of the 'search' parameter beyond the schema's generic examples. This enhances understanding of how to construct effective queries, though it doesn't fully compensate for all behavioral gaps.

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: 'Search medical device establishment registrations & listings (336K+ records). Where devices are manufactured and which devices are made at each establishment.' It uses specific verbs ('Search'), identifies the resource ('medical device establishment registrations & listings'), provides scale context ('336K+ records'), and distinguishes its scope from potential siblings by focusing on manufacturing locations and product associations. This is comprehensive and unambiguous.

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 implied usage through example searches (e.g., 'products.product_code:HQY', 'products.openfda.regulation_number:886.5850'), which suggest when to use this tool for querying specific fields. However, it lacks explicit guidance on when to choose this tool over alternatives (e.g., other FDA-related tools like fda_device_510k or fda_device_recalls) or any prerequisites. The examples are helpful but not sufficient for clear differentiation from siblings.

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