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

Annotations already declare readOnlyHint=true, and 'Non-mutating computation' largely restates that rather than adding new behavioral detail. The Engine API endpoint mapping (POST /suggest) is modest added context, but nothing about return shape, rate limits, or auth is disclosed.

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?

Three short, front-loaded sentences with the purpose stated first. Slightly marred by 'Non-mutating computation,' which duplicates the readOnlyHint annotation instead of contributing new information.

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 tool with 8 parameters (including nested evidence objects) and no output schema, the description says nothing about what the suggestions look like (observation IDs, likelihood, source flags) that an agent would need to consume the result. Adequate on the request side, incomplete on the response side.

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 description coverage is 88%, so the schema itself documents nearly every parameter (age, sex, evidence, suggest_method, etc.) in detail. The description adds no parameter-level meaning beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('suggest additional symptoms/observations the patient is likely to have') plus the goal ('speed up the interview'). This clearly separates it from siblings like infermedica_diagnosis or get_symptom, though no sibling is named explicitly.

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?

'To speed up the interview' implies the workflow context where this tool fits, but there is no explicit when-to-use/when-not or named alternative among the many sibling tools. Usage is inferable but not spelled out.

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