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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds scope context (which engines and signals are inspected), but discloses no behavioral traits such as rate limits, whether the check is live vs cached, or how long it takes. Adequate but not rich beyond the annotations.

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?

A single front-loaded sentence with the tool's label ('AEO check:') first and no filler. The parenthetical engine list is dense but earns its place by scoping the check.

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?

The description is adequate for a one-parameter read-only check, but with no output schema present it leaves the result shape undefined – an agent cannot tell whether it gets a pass/fail, a per-engine breakdown, or the raw llms.txt/structured-data findings.

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% with a single required 'url' parameter whose format and meaning are fully documented in the schema. The description adds no syntax, format, or constraint detail beyond it, 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 (check) and a specific resource/domain (AI answer-engine crawlability and citation), and enumerates the concrete signals examined (GPTBot, Claude, Perplexity, Google-Extended, llms.txt, structured data). This is clearly distinguishable from siblings like check_seo or check_ssl, though it never explicitly contrasts itself with them.

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 description implies when the tool is relevant (whenever AEO/AI-crawlability matters) but gives no explicit when-to-use, when-not-to-use, or alternative-selection guidance relative to check_seo, scan_website, or the other check_* tools. Usage is left to inference from the purpose statement.

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