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 implies a read-only operation by describing metadata retrieval, but lacks details on error handling, rate limits, authentication needs, or response format. The description adds some context about the tool's role in discovery, but falls short of providing comprehensive behavioral traits for a tool with no annotation support.

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 front-loaded and efficiently structured in two sentences: the first states the core purpose, and the second provides usage context. Every sentence adds value without redundancy, making it appropriately concise for the tool's complexity.

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 low complexity (1 parameter, no output schema, no annotations), the description is largely complete for its purpose. It clarifies the tool's role in discovery and distinguishes it from data-querying siblings. However, without annotations or an output schema, it could benefit from more detail on response structure or error cases, slightly limiting completeness.

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%, with the input schema fully documenting the single 'endpoint' parameter. The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't clarify endpoint format constraints or examples). Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 with specific verbs ('Get field names, data types, and formats') and resource ('for a specific Treasury Fiscal Data API endpoint'). It distinguishes itself from sibling tools by focusing on metadata discovery rather than data querying, which is evident from the sibling list containing tools like 'query_fiscal_data' for actual data retrieval.

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 explicitly provides usage guidance by stating 'This helps you discover what fields are available before querying data.' This indicates when to use this tool (for discovery/preparation) versus alternatives (like 'query_fiscal_data' for actual data queries), offering clear context for its application.

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