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 states the tool retrieves data ('Get'), implying a read-only operation, but does not specify whether it requires authentication, has rate limits, returns paginated results, or details the output format (e.g., JSON structure). For a tool with no annotations, this leaves significant behavioral gaps, though it correctly indicates a data retrieval function without contradictions.

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 with the core purpose in the first sentence and uses a second sentence to provide clarifying examples, with no wasted words. Both sentences earn their place by enhancing understanding without redundancy, making it efficiently structured and 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 has no annotations, no output schema, and a simple input schema with one parameter, the description is moderately complete. It clearly states what the tool does and provides examples, but lacks details on behavioral aspects (e.g., data format, error handling) and does not fully compensate for the absence of structured metadata. For a read-only data retrieval tool, it meets minimum viability but has clear gaps in contextual information.

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 input schema has 100% description coverage for its single parameter ('limit'), documented as 'Number of specialties (default 30)'. The description does not add any parameter-specific information beyond what the schema provides, such as explaining how 'limit' affects the output or mentioning other implicit parameters. With high schema coverage, the baseline score of 3 is appropriate, as the description adds no extra semantic value for parameters.

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 national payment totals and averages') and resources ('by medical specialty'), and distinguishes it from siblings by specifying it focuses on specialty-level aggregation rather than company, hospital, physician, or other dimensions present in sibling tools like 'open_payments_by_company' or 'open_payments_by_physician'.

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 context by mentioning 'national payment totals and averages' and examples like 'cardiologists, orthopedic surgeons, psychiatrists', suggesting it's for analyzing specialty-level pharma payments. However, it does not explicitly state when to use this tool versus alternatives (e.g., 'open_payments_summary' or 'open_payments_top'), nor does it provide exclusions or prerequisites, leaving the agent to infer from examples.

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