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

With no annotations, the description carries the burden. It discloses that the tool returns a score (0-100), performs checks, returns itemized pass/fail results with fixes, and mentions rate limits and payment for high-volume calls. It also implies it makes HTTP requests to the target URL. It does not mention side effects or error handling, but given the nature, it covers the key behavioral aspects.

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 moderately long but every sentence adds value: purpose, checks performed, output, use cases, and pricing/rate limits. It is front-loaded with the core function and then provides supporting details. No filler or tautology, though it could be slightly shortened without losing essential information.

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?

Given the tool has a single parameter and no output schema, the description adequately explains what it does, what it checks, what it returns (itemized checks with pass/fail and fixes), and when to use it. It also addresses usage restrictions (rate limits, payment) and provides a link for production use. This is a complete description for a simple tool.

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 the schema already explains the URL format and default scheme handling. The tool description does not add additional parameter details beyond restating the purpose. Per guidelines, the baseline is 3 when the schema covers parameters well; no extra value is added here.

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 specific verb and resource: 'Score any website 0-100 on how ready it is for AI agents' and then lists concrete checks (robots.txt, llms.txt, structured data, etc.). This clearly distinguishes it from siblings like check_wellknown_discovery or generate_llms_txt by focusing on a holistic readiness score rather than a single file check.

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?

Explicit use cases are provided: 'Use it to audit a merchant site, compare competitors, or generate an agentic-SEO to-do list.' It also gives practical guidance on rate limits (free tier self-limit) and alternative payment for high-volume use. It does not explicitly state when not to use it or name alternatives, but the context is clear enough.

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