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

Annotations already declare it is a non-read-only, non-idempotent, non-destructive operation, so the safety profile is covered. The description adds genuinely new behavior: monthly usage limits (quota constraint) and the asynchronous 30-60s processing model, which an agent needs to plan a poll.

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?

Front-loaded with the purpose, then behavior, then sibling routing, then args. The Args block partly restates the required flags already in the schema, a minor redundancy, but overall the text is tight and well ordered.

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?

No output schema exists, but the description explains the async flow and points to the results tool, so an agent knows what to do after invoking. Combined with annotations covering safety and the quota/timing disclosure, it is nearly complete for a start-an-async-job tool.

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 only 33%, so the description must compensate. It adds a real constraint the schema lacks (query is 3-500 characters) and labels both required params, but brand_id is only glossed as 'brand context' and user_intent is not addressed (though the schema documents it). Adequate but with gaps.

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 states a specific verb and resource ('Diagnose a specific search query across AI models') and enumerates exactly what the diagnosis produces (model responses, brand presence, competitors, cited sources). It clearly separates this action tool from the retrieval sibling get_diagnosis_result.

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?

It explicitly routes the agent to get_diagnosis_result for checking results and states the 30-60 second processing window, which tells the agent this is an async start-then-poll tool. It lacks explicit when-not-to-use guidance, but the workflow context is clear.

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