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

Beyond the readOnly/idempotent annotations, the description discloses failure behavior and latency: 'bundlephobia's first measurement on a new version can take 5-30s', 'Partial failures degrade gracefully', and 'sources_failed will list it if it times out'. These are valuable operational traits not inferable from annotations alone.

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 every sentence earns its place: it covers the composite workflow, trigger phrases, returned fields, ecosystem scope, and error handling. It is front-loaded with the primary purpose and contains no filler 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 (fans out to two external services, optional version parameter, no output schema), the description compensates well by enumerating the summary block fields, explaining partial-failure semantics, and noting the first-call latency. It gives an agent enough context to invoke the tool correctly and interpret results.

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 the schema already fully documents both parameters (package name with scoped-package support, version with example). The description only uses illustrative examples ('lodash', '18.3.1') and adds no additional semantic meaning beyond the schema, so the baseline score 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 specific verb and resource: 'Composite "should I add this npm package to my project" check in ONE call' and explicitly names the data sources (deps.dev, bundlephobia). This clearly distinguishes it from sibling research tools by focusing narrowly on npm dependency evaluation.

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?

Provides explicit when-to-use guidance: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. It also gives a concrete alternative for non-NPM ecosystems: 'PyPI / Maven / Cargo / Go fall under deps.dev:version directly', making the usage boundary clear.

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