US Government Open Data MCP

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

Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds useful behavioral context by specifying the return fields (trial ID, title, status, etc.) and providing an example use case for sponsor filtering, but it does not disclose pagination behavior, rate limits, or error handling, which are gaps given the lack of output schema.

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 efficiently structured in two sentences: the first states the purpose and parameters, and the second provides a usage example. Every sentence adds value without redundancy, making it front-loaded and appropriately sized 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 moderate complexity (9 parameters, no output schema, rich annotations), the description is mostly complete. It covers purpose, usage, and return fields, but lacks details on output format, pagination (implied by page_size but not explained), and error cases, which slightly reduces 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 detailed descriptions and enums for parameters like status and phase. The description adds minimal value beyond the schema by listing filterable fields and giving an example for sponsor, but it does not explain parameter interactions or default behaviors, aligning with the baseline 3 when schema does the heavy lifting.

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 specific action ('Search ClinicalTrials.gov') and resource ('clinical trials'), enumerates the searchable fields (condition, drug/intervention, sponsor, status, phase), and distinguishes it from sibling tools like 'clinical_trials_detail' and 'clinical_trials_stats' by emphasizing its search functionality rather than detailed retrieval or statistical analysis.

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 clear context for when to use the tool ('to track pharma company research') and implicitly suggests alternatives by mentioning specific filters, but it does not explicitly name when not to use it or list alternative tools like 'clinical_trials_detail' for deeper information, keeping it at a 4.

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