clinical_trials_detail

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

Annotations include readOnlyHint=true, confirming the tool is read-only. The description adds value by explaining the 'fields' parameter's behavior (reducing response size), which is a performance-relevant trait.

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, each serving a distinct purpose: stating purpose, listing returns, and providing usage guidance. It is front-loaded and contains no superfluous words.

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 absence of an output schema, the description lists the major sections returned, providing adequate context. However, it could be more specific about the structure of the response. Still, it is sufficient for an agent to understand what to expect.

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 covers both parameters with descriptions (100% coverage). The tool's description adds context beyond the schema by framing the 'fields' parameter as a way to request 'specific sections', which is a slight improvement over the schema's technical description.

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 action ('Get full details for a specific clinical trial by NCT ID') and enumerates the types of information returned (protocol, eligibility, arms/interventions, design, locations, contacts, oversight info). This distinguishes it from sibling tools like clinical_trials_search, which returns summaries, and clinical_trials_results, which likely returns result data.

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 explicitly advises using the 'fields' parameter to request only specific sections to reduce response size. While it does not mention when to avoid this tool in favor of siblings, the context is clear for a detail retrieval by ID.

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