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

Description adds rich behavioral context beyond annotations: 'Partial failures degrade gracefully', 'bundlephobia's first measurement on a new version can take 5-30s', and 'sources_failed will list it if it times out'. This explains latency and error handling, complementing the read-only/idempotent annotations without contradiction.

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, with each sentence adding value. It front-loads the core purpose, then usage, return format, ecosystem scope, and failure behavior. Slightly long but every sentence earns its place; no redundant words.

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 thoroughly explains the return value: summary block with specific fields, per-advisory detail, links, and recent versions. It also covers ecological limitations, latency, and partial failure handling, making it complete for a 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?

Schema description coverage is 100%, so baseline is 3. Both parameters are adequately described in the schema (package name, version defaulting to latest). The description does not add new parameter semantics but reinforces context by mentioning npm ecosystem and return fields like is_latest.

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's function: a composite 'should I add this npm package' check that fans out to deps.dev and bundlephobia. It specifies the data sources and what each contributes, distinguishing it from sibling tools like deep_research or validate_claim.

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: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' Also provides exclusions and alternatives: '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.