Measure lab performance

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains that Playwright is required, that the tool returns an install command if missing, and that the data is lab data. This gives useful context beyond the basic action, though it does not cover every possible behavior like output format or side effects.

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 two sentences long, front-loaded with the action, and every sentence adds value without redundancy. It is concise yet comprehensive for its scope.

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 single parameter and no output schema, the description is fairly complete: it names the metrics captured, the dependency, and the failure mode. However, it does not describe the exact return format on success, which would be helpful since there is no output schema.

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 schema description covers 100% of the single parameter (url) with type and example. The description adds no extra parameter-level meaning, so the 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 uses a specific verb ('Load the page... and capture') with a clear resource and explicit list of metrics (TTFB, FCP, LCP, CLS, load times, request count, transfer sizes). This distinguishes it from sibling tools like analyze_page_weight or check_headers.

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 clarifies this returns lab data, not field data, and states the prerequisite of the Playwright Chromium browser. However, it does not name alternative sibling tools or explicitly state when to use this tool over them, so it stops short of a 5.

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