AI crawler audit

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

With no annotations provided, the description carries the full behavioral burden. It usefully discloses what is inspected and that it returns a 0-100 score with per-crawler verdicts, but it does not state whether the tool performs a live network fetch, has rate limits, or how failures are handled.

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 description is two tight sentences, front-loaded with the core purpose and followed by the return value. Every phrase contributes to understanding what is audited and what comes back.

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 description explains the checks performed and the shape of the return value, which is important because no output schema exists. It is largely complete for a simple single-parameter audit tool, though it could clarify operational behavior such as live fetching or scoring composition.

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?

There is only one parameter, url, and the schema description coverage is 100%, so the schema already documents its meaning and format. The description adds no parameter-specific details beyond the general audit context, making the baseline score of 3 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 states a specific verb and resource: auditing a site for AI search visibility, including robots.txt treatment of named AI crawlers and llms.txt existence. It is clear what the tool does, but it does not explicitly differentiate itself from the sibling list_ai_crawlers tool.

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 use case is implied by “Audit a site for AI search visibility,” but there is no explicit guidance on when to use this tool versus list_ai_crawlers or when not to use it. The agent can infer the context, but alternatives and exclusions are not stated.

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