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

Beyond annotations (readOnly, openWorld, idempotent), the description discloses key behavioral traits: it fans out to multiple sources, handles partial failures gracefully, notes that bundlephobia's first measurement can take 5-30s, and explains that sources_failed will list timeouts. This adds substantial context not available in 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, front-loading the core purpose and then logically covering usage, return values, ecosystem scope, and error handling. Every sentence contributes unique value with no fluff 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?

Given the tool's complexity and lack of output schema, the description thoroughly covers return values (summary block fields, per-advisory detail, links, alternative versions), error handling, and performance caveats. This is sufficient for an agent to understand what to expect and how to handle edge cases.

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 provides 100% coverage of both parameters (package and version) with clear descriptions, including scoped packages and default behavior. The description does not add additional semantic meaning beyond restating the schema, so 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 the tool is a composite check for deciding whether to add an npm package, listing specific data sources (deps.dev, bundlephobia) and the types of information gathered. It distinguishes itself from siblings by focusing solely on npm dependency scanning, with no overlap.

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 states when to use it: whenever an agent asks 'is X safe / popular / small' or 'what does adding lodash cost me'. Also provides exclusion guidance, noting the NPM ecosystem only in v1 and directing other ecosystems to 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.