clinical.trial-search

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

No annotations provided, so the description must disclose behavior. It notes the dataset (ClinicalTrials.gov) and coverage, but does not discuss rate limits, data freshness, pagination behavior, or result structure beyond what the schema implies.

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 extremely concise—two sentences that front-load the purpose and key details. Every sentence adds value without redundancy.

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 8 parameters and no output schema, the description is adequate but not fully complete. It covers the core use case and filters but omits explanation of output format or pagination details.

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 low (13%), and the description adds value by grouping filters (recruitment status, sponsor, phase, country) and clarifying query modes (free-text or NCT ID). However, it does not describe pageSize or pageToken, which are important for pagination.

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 identifies the tool as searching ClinicalTrials.gov for clinical studies, specifying the scope (US and international, ~500k studies). It distinguishes from sibling tools by being domain-specific and mentions query methods and filters.

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 states when to use (for clinical trials) and lists query methods and filters, but does not provide explicit guidance on when not to use or alternatives. The context is clear but lacks exclusions.

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