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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds genuinely new behavioral context: the return shape (0-100 score, grade, prioritised recommendations) and the $0.02 per-call x402 payment requirement, which an agent must know before invoking.

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?

Front-loads the purpose, then the enumerated signals, then the return value, intended use, and price — each clause carries distinct information with no filler. The signal list is long but is the substantive payload the agent needs to judge relevance.

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 steps in to describe the return (score, grade, recommendations), and it discloses the payment model and audit scope. An agent has everything needed to decide to call it, form the URL argument, and anticipate cost and result.

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 single parameter already documents that a URL or bare domain is accepted with an example. The description adds only the scope constraint "one web page" — no syntax or normalization details beyond the schema, so the baseline 3 applies.

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 and resource — auditing one web page's visibility to AI search engines — and enumerates exactly what is inspected (crawler rules, llms.txt, sitemap, on-page signals). This clearly distinguishes it from narrower siblings like llms_txt_check and ai_crawler_matrix, which cover only one slice of what is audited here.

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?

"Use it to check or monitor a site for generative-engine optimisation" gives a concrete usage context and implies repeated/monitoring use. It stops short of naming alternatives or exclusions (e.g. when to prefer llms_txt_check for a single-file check), so it is clear but not fully routing.

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