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

Annotations already declare readOnly, idempotent, open-world, non-destructive, so safety is covered structurally; the description adds real behavioral context by listing the external signals it fetches and the exact components of the response (score, grade, per-category breakdown, issues, raw signals). It does not cover things like rate limits, latency, or behavior on unreachable/blocked URLs, so it stops short of a 5.

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-loaded with the core purpose and return payload, then scoping, then an example question. Paragraph breaks map cleanly to purpose / usage / boundary / example, and every sentence contributes information an agent can act on.

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 and a single trivial parameter, the description carries the burden well: it explains what is checked, what comes back, what the scope excludes, and when to trigger it. Nothing needed to call this tool correctly is missing.

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?

Only one parameter, and the schema already documents it at 100% coverage ('a full URL or a bare domain such as example.com'). The description reinforces this through the bare-domain example question but adds no new syntax or edge-case meaning, so the baseline applies rather than a bonus.

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 concrete verb+resource ('Check how ready one web page is to be read and cited by AI assistants') and enumerates the signals inspected: robots.txt / GPTBot, ClaudeBot, PerplexityBot, Google-Extended, llms.txt, sitemap, structured data, headings, trust signals, meta tags, Wikidata. It also names the return shape (score 0-100, A-F grade, per-category scores, issues, raw signals), so an agent can distinguish it from brand-visibility siblings without opening any schema.

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?

Gives explicit triggering conditions with user-phrase examples ('audit our homepage for AI', 'can ChatGPT crawl our site', 'GEO check of example.com'), plus an explicit exclusion: it checks the page itself and does not measure what assistants answer about a brand, which needs a Refora workspace. That is when-to-use, when-not-to-use, and a pointer to the alternative in one place.

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