clinical_trials_stats

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

The readOnlyHint annotation covers safety, and the description adds that it queries 8 statuses in parallel, which is a useful behavioral detail beyond the annotation. It also discloses flexible input types (disease or drug), aiding the agent in anticipating tool behavior.

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 four sentences, front-loaded with the main action, and contains no redundancy. Every sentence adds value, covering purpose, output nature, input flexibility, and implementation behavior.

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?

The tool is simple (2 params, read-only, no output schema). The description sufficiently conveys the output type (count breakdown by status), input types, and parallel querying behavior. It doesn't list the exact 8 statuses, but the examples and 'etc.' imply the breakdown is comprehensive.

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 schema already provides 100% parameter coverage with descriptions. The description's examples ('breast cancer', 'semaglutide') overlap with schema examples and don't add significant new meaning beyond what the schema offers. Baseline 3 is appropriate.

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 explicitly states the tool produces a trial count breakdown by recruitment status for a condition or drug, clearly identifying its function. It distinguishes itself from sibling clinical trial tools (search, detail, results) by focusing on aggregated statistics rather than lists.

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 provides clear context: it is for count breakdowns by recruitment status and works with both diseases and drug names. It doesn't explicitly name alternative tools, but the 'breakdown' focus and mention of parallel status queries make the use case clear.

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