US Government Open Data MCP

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

Annotations provide readOnlyHint=true, indicating a safe read operation. The description adds value by characterizing the reports as 'authoritative, nonpartisan' and 'gold standard', which gives context about data quality. However, it does not disclose behavioral traits like pagination (implied by 'limit' parameter), rate limits, authentication needs, or error handling. With annotations covering safety, the description adds some context but lacks operational details.

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 highly concise and front-loaded: a single sentence states the core purpose, followed by two brief sentences adding qualitative context. Every sentence earns its place by enhancing understanding without redundancy. It is appropriately sized for a simple retrieval tool.

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 complexity (simple retrieval with 3 optional parameters), annotations (readOnlyHint=true), and no output schema, the description is minimally adequate. It covers the 'what' but lacks details on 'how' (e.g., output format, pagination, error cases) and usage context. With annotations handling safety, it meets basic needs but leaves gaps for effective agent operation.

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 clear documentation for 'limit', 'fromDateTime', and 'toDateTime' parameters. The description does not add any parameter-specific information beyond what the schema provides (e.g., it does not explain date filtering semantics or default behaviors). Baseline 3 is appropriate since the schema fully describes parameters, and the description does not compensate or add extra meaning.

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: 'Get Congressional Research Service reports' (verb + resource). It adds context about the reports being 'authoritative, nonpartisan analysis on legislative topics' and 'the gold standard for policy research', which helps distinguish it from other data tools. However, it does not explicitly differentiate from sibling tools like 'congress_crs_report_details' (which appears in the sibling list), so it misses full sibling differentiation.

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 no guidance on when to use this tool versus alternatives. It does not mention sibling tools (e.g., 'congress_crs_report_details' for detailed reports or other congress_* tools), prerequisites, or specific use cases. The agent must infer usage from the purpose alone, which is insufficient for effective tool selection.

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