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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds significant context about external API calls, partial failure degradation, the 5-30s latency for bundlephobia's first measurement, and the sources_failed field—information beyond the annotations that helps set expectations.

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 long but every sentence contributes value: purpose, usage triggers, output summary, ecosystem caveat, and failure behavior. The semicolon-separated field list in parentheses keeps the return summary compact and scannable.

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?

With no output schema, the description enumerates the returned summary block fields, per-advisory detail, links, and recent alternative versions. It also covers operational caveats (performance, partial failures) and scope limitations, making it nearly complete for an agent selecting and invoking the tool.

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%, and the schema already documents both the required package name and version defaulting behavior. The description does not add new parameter-specific semantics beyond reinforcing the composite nature, so the baseline score 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 opens with a specific verb and resource: a composite check for adding an npm package, explicitly naming deps.dev and bundlephobia. It also states the ecosystem boundary ('NPM ecosystem only in v1'), which clearly distinguishes it from generic research tools.

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 an explicit trigger: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also provides an exclusion for other ecosystems (PyPI/Maven/Cargo/Go) and directs them to deps.dev:version directly, which is a clear alternative.

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