lighthouse_analyze

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

The description mentions that analysis may take a few seconds, which is a useful behavioral hint. However, it does not disclose other traits such as being read-only, error handling for invalid URLs, or whether authentication is required. With no annotations, more details would be beneficial.

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?

Three concise sentences with no redundancy. The verb is front-loaded, and every sentence provides essential information without waste.

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?

The description covers the basic function and duration but lacks details on the return format or structure of scores. Since there is no output schema, the description should ideally specify what the return object looks like. Adequate for a simple tool but could be more complete.

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%, so the schema already describes each parameter. The description does not add additional meaning beyond restating the categories. Baseline of 3 is appropriate.

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 it runs Google Lighthouse analysis on a URL and returns scores for performance, SEO, accessibility, and best-practices. This distinguishes it from sibling tools like check_accessibility and get_seo_recommendations which focus on specific aspects.

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?

No guidance on when to use this tool versus siblings. For example, it doesn't mention that for detailed accessibility checks or SEO recommendations, other tools like check_accessibility or get_seo_recommendations might be more appropriate.

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