clinical_trials_field_sizes

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

The description is consistent with the readOnlyHint annotation, and it adds value by disclosing the output includes min/max/top sizes for array fields, providing behavioral context beyond the annotation.

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 three sentences long, front-loaded with the action, and every sentence serves a purpose—explaining what the tool does, what it shows, and its utility.

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 simplicity (one optional parameter, no output schema), the description adequately covers functionality and common use cases. It could be more specific about output format, but overall it is sufficient.

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 already covers the single optional 'fields' parameter with a clear description. The description does not add new semantic meaning beyond mentioning example fields, so it meets the baseline for high schema coverage.

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 retrieves 'statistics on list/array field sizes' from ClinicalTrials.gov, citing specific fields like Condition, Intervention, Phase. It distinguishes itself from other clinical trial tools by focusing on field size distributions, though it does not explicitly differentiate from similar siblings like clinical_trials_field_values.

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 includes the phrase 'Useful for understanding data distribution,' which implies when to use the tool, but it lacks explicit guidance on when not to use it or alternatives among sibling tools.

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