Audit a site the way a search engine and an AI read it

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

With no annotations, the description carries the full burden and does well: it discloses the read-only nature of the operation, that only free public signals are used, that no account is needed, and that nothing is stored. It omits runtime/rate behavior and any failure modes, which keeps it below 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?

Three dense sentences, front-loaded with the verb and the scoring scope, followed by output content and then usage triggers. Every sentence earns its place; the parenthetical explanations of AEO/GEO add clarity without much bloat.

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?

There is no output schema, so the description must explain returns, and it does: six scores out of ten plus every failing and borderline check with observed findings. Combined with the schema documenting all three parameters, an agent has nearly everything needed to call it correctly.

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 coverage is 100%, so url, lang, and pages are all documented in the schema, making 3 the baseline. The description adds only the general notion of reading a public site and samples from the sitemap, no extra per-parameter meaning.

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 (read a public site and score it) and enumerates the six scoring areas, which is far more specific than a tautology. It does not name or differentiate against siblings like compare_sites or check_llms_txt, so it stops short of the 5 bar for explicit sibling distinction.

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 three concrete trigger scenarios ('why a site is not being cited', 'why AI assistants recommend competitors', 'what to fix first'), which is clear context for invocation. It offers no when-not conditions and does not route to the alternative siblings, so it is not a full 5.

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