Check AI Readiness

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

Annotations already declare readOnlyHint=true and openWorldHint=true, and the description is consistent with these. It adds substantial behavioral context by enumerating exactly what checks are performed (AI crawler access, file detection, structured data, meta signals) and the output contents. This goes beyond the annotations, which only signal safety, not the scope of the audit. No 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?

Two sentences, no redundancy. The first sentence front-loads the core action and return payload; the second provides usage guidance. Every word earns its place, and the structure naturally surfaces the important 'first step' instruction.

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 no output schema exists, the description fully enumerates the output components (score, per-crawler status, AI-specific files, structured data, meta signals, fix list), which is essential for the agent to understand what to expect. The one parameter is well-covered by the schema. The usage context is clear. Nothing an agent needs to invoke 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?

Schema coverage is 100% – the schema fully describes the 'url' parameter. The description only refers to 'a website' without adding format or constraints beyond the schema (e.g., no mention of protocol handling or query string). Baseline 3 is correct when the schema carries the parameter documentation, and the description adds no extra semantic value.

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 states a specific verb ('Check') and resource ('AI crawlers can access a website'), then enumerates the detailed return values (readiness score, per-crawler status, AI-specific files, structured data, meta signals, fix list). This clearly distinguishes it from sibling validators (validate_robots, validate_schema, etc.) as a comprehensive first-step audit, not a single-aspect check.

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?

It explicitly tells the agent to 'Use this as the first step in any AI SEO audit', giving clear positional guidance among siblings. It does not explicitly list when NOT to use it (e.g., for deep validation of a single aspect, use validate_robots), but the first-step framing implies that granular validators follow. A minor gap, so a 4 is appropriate.

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