fix_site

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

With no annotations, the description carries the full burden. It clearly discloses a required API key, cost per call, that output is generated code for coding agents to apply, not an applied change, and the score/ceiling/reference structure. This is good 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?

Each sentence delivers a distinct piece of information: purpose, return value, score projections, content recommendations, format guidance, cost/key. The description is detailed but not bloated, and important usage constraints are front-loaded.

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 presence of an output schema and the simple interface (3 parameters, 1 required), the description is mostly complete: it clarifies behavior, cost, authentication, and output format. It falls slightly short on documenting the 'pages' parameter and on explicit alternatives coverage.

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?

Input schema param descriptions are 0% coverage, so the description must compensate. It only mentions how to use 'format' (set to 'claude_code'), and says nothing about 'url' or 'pages'. The meaning of 'pages' is not clarified anywhere.

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 opens with a specific verb ('Generate') and a clear resource ('complete fix code for all AI visibility issues across AEO, GEO, and Agent Readiness'). This distinguishes it from sibling tools like scan_site or audit_site, which obviously cover diagnosis rather than fix generation.

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 implicit usage is to generate code fixes after AI visibility issues have been found, but the description does not explicitly state when to use it versus alternatives like scan_site, audit_site, or compare_sites. No exclusion or condition selection is given.

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