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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the audit's core behavior (analyzes whether engines will cite the project, identifies gaps stopping it) and details the return values: a 0–100 citeability score, per-engine read, per-rule analysis, and ranked fix list. It does not mention rate limits or auth, but as a read-only audit tool, the key behavior is well covered.

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?

The description is four sentences, each conveying useful information: the action, the analysis performed, the output structure, and a positioning statement. It is efficiently structured and front-loaded with the key purpose. The final 'successor to SEO' phrase is slightly extraneous but not distracting.

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?

Given there is no output schema, the description compensates by clearly listing the output components (citeability score, per-engine read, per-rule analysis, ranked fix list). It also mentions the 12 rules. However, it does not clarify that at least one of url or text is needed for the audit, which is a minor omission for completeness.

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%, so the input schema fully documents the three parameters (url, text, asset_type). The description adds no additional parameter-specific details beyond the schema, but it does mention the audit scope in general. This meets the baseline of 3, but doesn't exceed it.

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?

The description explicitly states it runs an AEO/GEO visibility audit with 12 rules, analyzing whether AI answer engines (ChatGPT, Perplexity, Claude, Gemini) will cite the project. This clearly differentiates it from sibling tools such as run_gdpr_pro_check or run_ad_creative_check, which target different domains.

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 provides clear context for when to use this tool: to assess AI answer engine citeability and identify gaps. It does not explicitly exclude alternatives, but the sibling tools are distinct regulatory/creative checks, making the use case unambiguous. The added note 'The 2026 successor to SEO' further implies its role in modern visibility auditing.

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