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

Annotations (readOnlyHint=true, openWorldHint=true) already establish this is a safe, open-world read, so the bar is lower. The description nevertheless adds genuinely useful context the annotations cannot: the call is paid via x402 at $0.004 USDC, which materially affects how an agent should invoke it. It stops short of covering rate limits, latency, or failure modes when a site block is absent.

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 sentences, front-loaded with the core question, then the concrete checklist, then the cost. Nearly every clause earns its place; the 'Generative-engine optimisation (GEO) in one call' line is partly positioning language, but it usefully ties the tool to a known term.

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?

With no output schema, the description carries the return-value burden and does so adequately by naming the output (a grade plus the exact fixes). Together with the enumerated checks, the pricing, and the read-only annotations, an agent has enough to invoke and interpret it; a hint at score range or response shape would close the remaining gap.

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 0%, so the single `url` parameter is undocumented in structured data. The description's framing ('How ready is a website for AI agents?') and the per-call pricing imply that the input is one public site URL, which is enough to call it correctly, but it adds no syntax, scheme, or normalization guidance (e.g. whether a scheme or trailing path is accepted).

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+resource — scoring how ready a website is for AI agents — and enumerates the exact artifacts checked (llms.txt, llms-full.txt, A2A agent card, MCP server, OpenAPI, x402, robots.txt AI policy, structured data). That enumeration cleanly separates it from near-siblings like seo, report_seo, domain_audit and x402_check, and it names the deliverable (a grade plus exact fixes).

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 question 'How ready is a website for AI agents?' implies the scenario clearly enough that an agent knows when to reach for it, but there is no explicit when-to-use framing, no when-not, and no pointer to alternatives such as seo/report_seo for classic SEO or x402_check for payment readiness alone. Usage is implied rather than stated.

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