mcp-seo-audit

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 effectively describes key behavioral traits: 'Processes sequentially with rate limiting,' 'Default quota: 200/day,' and the constraint on page types. However, it lacks details on error handling, response format, or confirmation of indexing success, leaving some gaps in transparency.

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 appropriately sized and front-loaded, with the first sentence stating the core purpose and key behavioral traits. The second sentence adds quota and constraints, and the 'Args' section efficiently documents parameters. Every sentence adds value without redundancy, making it concise and well-structured.

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 the tool's complexity (batch processing with constraints), no annotations, and an output schema present, the description is mostly complete. It covers purpose, usage, behavior, and parameters effectively. However, it could benefit from mentioning the output schema's role or a brief note on what to expect in the response, slightly reducing 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?

The input schema has 0% description coverage, so the description must compensate. It adds meaningful semantics: 'urls: List of URLs to index, one per line (max 100 per batch).' This clarifies the format (list, one per line) and constraint (max 100), which are not evident from the schema alone. However, it doesn't specify URL validation rules or examples, slightly limiting completeness.

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 specific action ('Request indexing for multiple URLs') and resource ('URLs'), distinguishing it from the sibling 'request_indexing' tool which presumably handles single URLs. It also specifies the scope ('multiple URLs') and constraints ('pages with JobPosting or BroadcastEvent structured data'), making the purpose highly specific and differentiated.

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 explicit guidance on when to use this tool: 'Only for pages with JobPosting or BroadcastEvent structured data.' It also implies an alternative by distinguishing it from 'request_indexing' (for single URLs) and sets clear constraints like 'max 100 per batch' and 'Default quota: 200/day,' helping users decide when to use it versus other options.

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