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

The description discloses important runtime behaviors beyond the annotations: it fans out across two services, may take 5-30s on first bundlephobia measurement, and degrades gracefully with sources_failed listing timeouts. This complements the readOnly/idempotent hints with latency and partial-failure semantics.

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 dense but well-structured: main purpose first, then return fields, then ecosystem scope and failure behavior. Each sentence adds distinct value, and the length is justified for a composite tool. No filler or repetition.

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 fully lists the return shape (summary fields, per-advisory detail, links, alternative versions), covers ecosystem limitations, and explains error handling. This gives an agent complete expectations for invocation and results.

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 coverage is 100% with descriptive parameter text for both package and version. The description adds no new parameter meaning beyond restating the default behavior; it does reinforce that version is optional and defaults to latest, but that's already in the schema. Baseline 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, outcome-oriented verb phrase ('should I add this npm package to my project' check) and enumerates the data sources (deps.dev and bundlephobia) and covered aspects (license, advisories, bundle size, etc.). This clearly distinguishes it from sibling tools like deep_research or validate_claim by stating its exact scope.

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?

Explicit usage guidance is provided: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also cautions that the tool is NPM-only in v1 and directs other ecosystems to deps.dev:version directly, offering a clear exclusion and alternative.

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