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

With no annotations provided, the description carries the full burden of explaining behavior. It does so by enumerating the checks performed and the output format. However, it does not disclose potential side effects (e.g., whether the tool fetches the URL, handles errors, or requires network access), which is a minor gap but not severe.

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 front-loaded with the main verb 'diagnose' and then efficiently lists checks and output. The final demo sentence adds context without excess. It is slightly longer than absolutely necessary but every sentence contributes value.

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?

Since there is no output schema, the description appropriately explains the return format (score and grade) and the key checks performed. The tool's complexity is moderate, and the description covers the essentials well, though it could note potential limitations (e.g., invalid URLs, network failures).

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 schema already describes both parameters with 100% coverage ('url' and 'intent'), so the baseline is 3. The description does not add extra meaning to the parameters beyond the tool's overall purpose; for example, it does not clarify what should go in 'intent' beyond the schema's vague 'why diagnosis is needed'.

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 clearly states a specific action: diagnosing how visible a website is to AI agents given a URL. It lists concrete checks (llms.txt, robots.txt, structured data, OGP, etc.) and the output (0-100 score, A-F grade). It is distinct from sibling tools, which focus on physical products, measurements, or searches.

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 provides a clear use context: it can be used as an AIO agency demo to show clients how AI sees their products. However, it does not explicitly state when not to use the tool or mention alternative tools, so it stops short of a full 5.

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