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

Beyond the annotations (which only flag a non-readonly, non-idempotent, open-world call), the description discloses that the preview runs nothing, that the approved call executes in the background for several minutes, that it consumes one of the account's allotted AI measurements, and that the site itself is unchanged. These are the exact quota, latency, and side-effect facts an agent needs and annotations cannot convey.

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 purpose is front-loaded and the closing reassurance ('Nothing on your site changes') earns its place, but the middle sentences are long and pack the preview/approval/workflow rules into dense clauses that could be broken apart for faster scanning.

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 has an output schema, full parameter documentation, and meaningful annotations; the description still covers the quota cost, async runtime, user-approval requirement, and next-step tool. Nothing an agent needs in order to invoke it correctly is missing.

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 100% and each parameter is thoroughly documented there, so the description only reinforces the approval parameter's preview-to-run relationship. With the schema doing the heavy lifting, the baseline 3 applies; the description adds no format or syntactic detail beyond it.

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 first sentence states a specific verb and resource ('measure whether AI assistants name one of your sites') and names the five engines covered. It also explicitly separates this tool from the sibling that reports results ('get_ai_visibility shows the result'), so an agent can distinguish them without opening schemas.

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 gives an explicit two-call protocol: call without approval for a preview, show the questions to the user, then call again with the approval code only after they agree. It also names the follow-up tool (get_ai_visibility) for retrieving the outcome, leaving no routing decision to inference.

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