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

With no annotations, the description carries the full burden, and it does substantial work: it discloses that the tool makes real HTTP requests, that Google-Extended and Applebot-Extended are treated as robots-only tokens with no server verdict, and that they are excluded from server-side counts. It does not mention failure modes, rate limits, or side effects, but the core behavior is clearly exposed.

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?

Every clause earns its place: it front-loads the tool's purpose, then explains the measurement method, the robots-token edge case, and the structure of `fixes`. Despite its length, nothing is redundant and the structure moves from output to method to caveats.

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?

Without an output schema, the description must define the return contract, and it covers the score, per-crawler verdicts, edge vendor, and fixes with important caveats. It stops short of describing exact response formatting, error behavior, or what happens on unreachable hosts, but for a one-parameter measurement tool the essentials are present.

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 already documents `host` clearly with the bare-domain requirement and an example, so schema coverage is 100%. The description adds domain-specific context but no new parameter semantics, so the baseline of 3 is appropriate.

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 opens with a concrete evaluation question and then enumerates specific outputs: readiness score, per-crawler verdicts with the three possible values, the answering edge vendor, and the `fixes` list. This makes the tool's function unambiguous and distinct from generic domain-measurement tools, even though sibling names are not mentioned.

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 when to use the tool: when you need a measured readiness answer based on real HTTP requests rather than guesses from robots.txt alone. However, it never names the sibling tools or states when not to use this tool, leaving the routing decision to the agent.

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