onto_validate_clinical

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

No annotations are provided, so the description must convey behavior. It states validation and matching display, but does not disclose whether the tool is read-only, what happens if the ontology is not loaded or crosswalk data is missing, or any side effects. The description is somewhat transparent but lacks depth.

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?

Two concise sentences with no redundancy. Every word adds value, clearly stating the action and outcome.

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?

For a simple tool with no parameters, the description covers the core purpose and result. However, it lacks context on prerequisites (e.g., loaded ontology and crosswalk data) and output format. Complete enough for basic use but could be more thorough.

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 has zero parameters, and schema coverage is trivially 100%. The description adds no parameter information, but none is needed. Per guidelines, baseline for 0 parameters is 4.

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 action ('Validate all class labels... against clinical crosswalk data') and the specific resource ('loaded ontology'). It also indicates what the output shows ('which terms match known clinical codes'), distinguishing it from sibling tools like onto_validate which does general validation.

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 the use case (clinical crosswalk validation) but provides no explicit guidance on when to use this tool versus alternatives like onto_validate or onto_crosswalk. No prerequisites, exclusions, or when-not-to-use information is given.

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