ai_citation_readiness

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

The description adds significant behavioral context beyond annotations: it explains the render-blindness check, evidence-backed signals, and mentions that schema.org/FAQ are informational and not scored. This complements the annotations (readOnlyHint, openWorldHint) without contradiction.

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 efficient and front-loaded with the core purpose. It is concise but could benefit from clearer sentence breaks or bullet points for readability. Currently, it reads as a single dense paragraph.

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 one parameter and no output schema, the description adequately explains what the tool does and its limitations (no guarantee of citation). However, it does not describe the return format or score range, which might be needed for an agent to interpret results.

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?

The input schema covers 100% of parameters with a clear description for 'url'. The tool description does not add additional meaning or usage tips for the parameter, so it meets the baseline for full schema coverage without extra detail.

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 clearly states the tool's purpose: scoring a page's readiness for LLM citation. It lists specific checks (render-blindness, statistics, etc.) and distinguishes itself from siblings like 'ai_citation_track' by focusing on readiness assessment rather than tracking.

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 implicit usage context by explaining the methodology (leads with render-blindness check) and notes that it does not guarantee citation. However, it does not explicitly list scenarios when not to use or compare with alternative tools.

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