clinical_trials_search

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

Annotations already declare readOnlyHint=true. The description adds value by stating the return fields (trial ID, title, status, phase, sponsor, conditions, enrollment, hasResults flag) and giving examples of specialized query syntaxes (Essie expressions and aggregation shorthands). It does not cover pagination or rate limits, but the schema already documents page_size and page_token.

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 five sentences, front-loaded with purpose, followed by return fields and targeted usage examples. Every sentence contributes meaningful information without redundancy or filler.

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 complexity (17 optional parameters, no output schema), the description provides a solid overview of search capabilities, return fields, and advanced usage examples. It complements the rich schema descriptions and gives an agent enough context to select and invoke the tool correctly for common use cases.

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 coverage is 100% with detailed parameter descriptions, so the baseline is 3. The description goes beyond by providing concrete examples for sponsor ('Pfizer', 'Moderna', 'NIH'), filter_advanced ('AREA[StartDate]RANGE[2024-01-01,MAX]'), and agg_filters ('results:with,sex:f,healthy:y'), which enhance practical understanding of how to use these parameters.

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 begins with 'Search ClinicalTrials.gov for clinical trials' and lists specific search facets (condition, drug/intervention, sponsor, status, phase, study type, location, title, or free text). This clearly distinguishes it from sibling tools like clinical_trials_detail and clinical_trials_stats, which have different primary functions.

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?

Provides clear context for use, including a concrete use case ('Use sponsor filter to track pharma company research') and guidance for advanced parameters (filter_advanced, agg_filters). However, it does not explicitly mention when to use alternative sibling tools (e.g., clinical_trials_detail for full trial details), so it lacks an explicit when-not-to-use statement.

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