clinical_trials_field_values

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds that results include 'top values, counts, and distributions' and gives concrete examples of return-style behavior, but it does not disclose potential limitations like pagination, result caps, or special field formatting. This is adequate but not rich.

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?

Three sentences, with the first and third providing core value. The phrase 'Powerful analytics tool:' is mild marketing fluff, but the description remains tight and front-loaded with the primary purpose.

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 simple 2-parameter schema, good annotations, and absence of an output schema, the description is reasonably complete. The examples clarify expected output behavior (count by phase, top conditions), which helps an agent anticipate return values without an 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?

Schema description coverage is 100%, so the baseline is 3. The schema already explains both fields (pipe-separated names) and types (enum of field types). The description adds usage examples but no additional parameter semantics beyond what the schema provides.

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 opens with a specific verb and resource: 'Get value statistics for study data fields — top values, counts, and distributions.' This clearly distinguishes it from sibling clinical trials tools like search or detail, and examples such as 'fields="Phase" shows trial count by phase' reinforce the unique analytics purpose.

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 gives clear context for when to use the tool ('find top conditions, top sponsors, phase distributions'), which implies the analytics use case. It does not explicitly name alternatives or exclusions, but the context is unambiguous enough for an agent to select it over the many sibling clinical trial tools.

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