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

With no annotations, the description carries the burden and does so well: it discloses the request is made under AI-crawler user agents and enumerates the four possible verdicts. The closing line 'A 200 is reachability, not visibility' usefully prevents misreading the result, though auth needs and rate/timeout behavior remain unstated.

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 tight sentences, front-loaded with the action and outcome set, then the scope exclusions and the interpretation caveat. No filler or repetition.

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?

There is no output schema or annotations, so the description must cover the return semantics — and it does by naming the four verdicts and warning against reading a 200 as visibility. It is nearly complete for a one-parameter diagnostic tool, missing only latency/auth/pagination context.

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?

One parameter with 100% schema description coverage ('Public http(s) URL'), so the schema already documents the only input. The description adds nothing about URL format or constraints beyond that, which is the expected baseline when the schema does the work.

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 (Fetch), a specific impersonation method (as GPTBot, ClaudeBot and other AI crawlers), and the exact reportable outcomes (allowed/blocked/challenged/not established). This clearly separates it from siblings like audit_page and crawl_site, which do not adopt crawler user agents.

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 draws firm negative boundaries — it does NOT measure citation likelihood, brand mentions, or ChatGPT ranking, clarifying when the result should not be interpreted. It stops short of naming which sibling to use for those related needs, so it is clear context without a routed alternative.

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