seo_audit

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It clearly explains the tool is a read-only analysis (audit) that returns results and suggests fixes for a feedback loop. It does not mention any destructive actions or authentication needs, which is acceptable for an audit tool. However, it could explicitly state that it does not modify any resources.

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 concise and well-structured, starting with the phase number and title. It uses bullet-like formatting for the categories and return values, making it easy to scan. Every sentence adds value, and there is no redundancy or fluff.

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 parameter count (7 with 100% schema coverage) and no output schema, the description provides sufficient detail about return values (score, grade, issue list with severity and fix instructions, top 5 recommendations). It also explains the pipeline integration and feedback loop. The tool is fully specified for its purpose.

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%, and the description adds significant value beyond the schema. For example, it explains that 'code' should be 'the complete page HTML from generate_full_page', and that 'js' and 'css' are for separate files. It provides context for parameters like 'industry' and 'pageType' for SEO recommendations, and explains the purpose of 'targetKeywords' for checking in headings and content.

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: analyzing generated HTML for SEO optimization and digital marketing readiness. It specifies it checks 50+ factors across 10 categories and returns a score, grade, issues, and recommendations. It also explicitly positions the tool in a pipeline: 'Call this AFTER generate_full_page, BEFORE review_output.' This distinguishes it from sibling tools like generate_background or plan_architecture.

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 when-to-use guidance: after generate_full_page and before review_output. It also explains the feedback loop: if the score is too low, re-run code generation with fixes. It mentions using industry and pageType parameters for context-aware checks, and suggests targetKeywords for checking. No alternatives are needed as siblings are unrelated.

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