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. It states this is a 'Get' operation (implying read-only) and describes the output format ('total amounts and number of payments per company'), but lacks critical behavioral details such as data source, update frequency, rate limits, authentication requirements, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its operational traits.

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 concise and front-loaded, consisting of two clear sentences that directly state the tool's purpose and output. There's no wasted language or redundancy. However, it could be slightly improved by integrating usage context, but as-is, it's efficiently structured.

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 (aggregated data retrieval), no annotations, no output schema, and 100% schema coverage, the description is minimally adequate. It explains what the tool does and the output format but lacks completeness in behavioral context, usage guidelines, and output details. It meets the bare minimum for a read operation but doesn't fully address the gaps left by missing annotations and output schema.

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, with the single parameter 'limit' well-documented in the schema. The description adds no parameter-specific information beyond what's in the schema, as it doesn't mention the 'limit' parameter or other potential inputs. With 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: 'Get payment summary data grouped by pharmaceutical/device company (all years combined).' It specifies the verb ('Get'), resource ('payment summary data'), and grouping criteria ('by pharmaceutical/device company'). However, it doesn't explicitly differentiate from its siblings like 'open_payments_by_hospital' or 'open_payments_by_physician' beyond the grouping field, missing a direct comparison.

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 mentions the grouping ('by pharmaceutical/device company') but doesn't specify use cases, prerequisites, or exclusions. For example, it doesn't indicate if this is for aggregated analysis or how it differs from other open_payments tools like 'open_payments_search' or 'open_payments_summary'.

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