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

Discloses additional behavioral traits beyond annotations: composite fan-out to two services, partial failures degrading gracefully, specific timeout behavior for bundlephobia's first measurement, and the sources_failed field. 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?

Single paragraph is dense but not overly long. Every sentence contributes useful information. Could be slightly better structured with bullets, but still concise and front-loaded.

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 complexity and no output schema, description adequately covers return fields (summary block with specific fields, per-advisory detail, links, alternative versions). Minor gap: not detailing per-advisory structure, but overall sufficient.

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%, so baseline is 3. Description adds minimal extra meaning by clarifying that version defaults to latest published when omitted. This is helpful but not extensive.

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?

Description clearly states the tool performs a composite check for npm package viability, covering license, advisories, version history, and bundle size. It distinguishes the tool from siblings by specifying its unique composite nature and ecosystem 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?

Explicitly tells when to use (agent asking about safety, popularity, size, cost) and when not (other ecosystems like PyPI, Maven, etc., fall under deps.dev:version). This provides clear usage boundaries.

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