US Government Open Data MCP

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what data is returned ('total pharma payments to teaching hospitals') but doesn't mention whether this is a read-only operation, potential rate limits, authentication requirements, data freshness, or pagination behavior. For a data retrieval tool with zero annotation coverage, this leaves significant behavioral 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 extremely concise with just two sentences that each add value. The first sentence states the core functionality, and the second provides context about usefulness. There's no wasted verbiage or repetition, making it efficiently front-loaded.

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 (grouped aggregation), no annotations, and no output schema, the description provides basic context but lacks important details. It explains what data is returned but not the format, structure, or limitations. For a tool with no structured behavioral or output documentation, the description should do more to compensate.

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% with one parameter (limit) fully documented in the schema. The description doesn't mention any parameters, which is acceptable since the schema provides complete parameter documentation. The baseline score of 3 reflects adequate parameter coverage through the schema alone.

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 payments grouped by teaching hospital' specifies the verb (get) and resource (payments grouped by teaching hospital). It distinguishes itself from siblings like open_payments_by_company or open_payments_by_physician by focusing on hospitals, but doesn't explicitly contrast with other hospital-related tools (though none are listed).

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 minimal usage guidance: 'useful for identifying institutional conflicts of interest' hints at a use case but doesn't specify when to use this tool versus alternatives like open_payments_summary or open_payments_search. No explicit when/when-not instructions or prerequisite information is provided.

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