clinicaltrials_get_study

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

The description extensively discloses behavioral traits beyond the annotations: return format including found, nctId, study with briefSummary, and _meta; error handling for 404 (found:false, study:null, never fabricated); honesty about leadSponsor.name being free text and nominal matching; plus warnings about schema_drift and outage behavior. This is highly transparent and informative for an agent.

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 well-structured with the purpose front-loaded. It covers parameter details, return structure, error cases, and caveats in a logical order. While slightly verbose due to extensive caveats, every sentence adds value and the conciseness is acceptable for the level of detail needed.

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 no output schema, the description fully describes the return structure (found, nctId, study, _meta) and error handling. It also addresses edge cases (nonexistent ID, schema drift, outage) and provides honesty notes. For a simple get-by-ID tool, this is comprehensive and leaves no critical gaps for agent decision-making.

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 nctId parameter with a detailed description (format, validation, return behavior). The description adds the URL path and restates some of the same information but does not provide substantial new meaning beyond what the schema already conveys. With 100% schema coverage, the baseline is 3, and the description adds only marginal value.

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 starts with 'Fetch ONE clinical study by its NCT id' which clearly specifies the action (fetch) and the resource (clinical study by ID). It distinguishes from sibling tools like clinicaltrials_search_studies by focusing on a single known study. The verb-resource combination is precise and unambiguous.

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 implies usage for retrieving a single study by NCT ID but does not explicitly state when to prefer this over alternatives like clinicaltrials_search_studies. It provides clear context about ID format validation and injection safety, but lacks an explicit when-to-use or when-not-to-use statement. Baseline 4 for clear context without exclusions.

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