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

Annotations already cover safety (readOnly, idempotent, non-destructive), but the description adds crucial behavioral details: partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed will list timeouts. It also describes what the return contains, going well beyond structured fields.

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 five dense sentences, each earning its place: composite nature, usage triggers, return format, ecosystem scope, and failure behavior. No filler or redundancy.

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?

Even without an output schema, the description fully enumerates the return structure (summary fields, advisory detail, links, alternative versions) and covers edge cases (timeouts, non-NPM ecosystems). For a multi-source composite tool, this is highly complete.

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% for both parameters (package and version), so the description does not need to add much. It mentions 'version history' and 'recent alternative versions', but does not add new meaning beyond the schema's own descriptions. Baseline 3 applies.

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' that fans out to deps.dev and bundlephobia, distinguishing it from sibling tools. It names specific services and data categories, making the purpose unambiguous.

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 gives an exclusion and alternative: 'NPM ecosystem only in v1; 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.