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

Beyond the annotations, the description discloses important behavioral traits: it fans out across multiple services, mentions latency ('bundlephobia's first measurement on a new version can take 5-30s'), and explains partial failure degradation ('sources_failed will list it if it times out, the rest still returns'). No contradiction with annotations.

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, opening with the core purpose and each sentence adding a distinct detail (output fields, ecosystem scope, failure handling). There is minimal redundancy, and every sentence earns its place.

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?

Since there is no output schema, the description compensates by enumerating the exact return fields ('summary block... per-advisory detail, links, and a list of recent alternative versions'). It also covers partial failure and latency, making it complete for a complex composite 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?

The schema already fully documents both parameters (package and version) with descriptions covering scoped packages and default version behavior. The description adds no significant parameter-level meaning beyond what the schema provides, so a 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 clearly states it is a 'Composite check' for 'should I add this npm package to my project' and enumerates the data sources and metrics. It distinguishes itself from siblings by explicitly naming the NPM-only scope and directing other ecosystems to a separate path.

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 given: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also provides a clear exclusion for non-NPM ecosystems: 'PyPI / Maven / Cargo / Go fall under deps.dev:version directly.'

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