estimate_bundle_size

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

The description mentions caching (24-hour in-memory) and queries to bundlephobia/npm registry, but omits details like network dependency, latency, or error handling. With no annotations, the description provides partial 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?

Two concise, well-structured sentences with no fluff. Key information is front-loaded and every sentence adds value.

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 tool is well-described for its purpose, but lacks details on the return value structure (e.g., whether result includes only sizes or other metadata). Given no output schema, the description could clarify the output format fully.

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 description adds significant value beyond the schema: explains tagName→package derivation, lists prefix mappings, warns about validation errors, and clarifies defaults for version and include_full_package. Schema coverage is 100%, and the description enhances usability.

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 estimates bundle size (minified + gzipped) for web components or npm packages, distinct from sibling tools which focus on accessibility, styling, or component analysis.

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 explicit when-to-use or when-not-to-use guidance is provided. Usage is implied by the task but no alternatives or exclusions are mentioned, leaving the agent to infer context.

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