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

Annotations already indicate read-only, idempotent, open-world, and non-destructive behavior. The description adds valuable context beyond that: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed lists timeouts. 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 a focused paragraph with a logical flow: purpose, usage, return fields, limitations, and failure behavior. Every sentence adds value, though it is dense and could benefit from bullet points for scannability. Still well-structured for the complexity.

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 no output schema, the description explains return values in detail (summary fields, advisories, links, alternatives), covers ecosystem scope, and clarifies partial failure behavior. It is complete for a composite tool with multiple data sources and 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?

Schema coverage is 100%, with both package and version already described. The description adds minimal new parameter meaning—it mentions 'is_latest' and defaults to latest, but the schema already states that version defaults to latest. Baseline 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 clear verb + resource: a composite check for whether to add an npm package, fanning out to deps.dev and bundlephobia. It distinguishes from sibling tools by explicitly targeting npm dependency evaluation, while siblings like scan_competitor_ai_presence cover different domains.

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 guidance: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"' and states NPM-only in v1, directing other ecosystems to deps.dev:version. This provides clear when-to-use and an alternative for non-NPM cases.

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