measure_coverage

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 states the tool returns per-file byte usage but does not mention potential side effects (e.g., whether it modifies page state) or prerequisites (e.g., page must be fully loaded). For a read-only measurement tool, this is adequate but lacks depth.

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, front-loading the key action and resource, and wastes no words. Every sentence serves a purpose: stating function, describing output, and listing use cases.

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 two parameters, no output schema, and no annotations, the description adequately covers purpose, output shape (per-file bytes used vs total), and applicability. It could mention return format details, but overall it is complete enough for an agent to understand invocation intent.

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?

With 100% schema description coverage, the baseline is 3. The description does not add additional meaning to the parameters beyond what the schema already provides (reset and type enums). It focuses on output instead.

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 measures JavaScript and CSS code coverage on the current page, specifying the verb (Measure) and resource (code coverage). It distinguishes from sibling tools like get_page_performance by focusing on coverage rather than performance metrics.

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 gives explicit use cases: identifying unused bundles, oversized dependencies, and optimization opportunities. While it doesn't explicitly state when not to use it or name alternatives, the context is clear enough for an agent to decide.

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