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

Beyond the read-only, idempotent, open-world annotations, the description discloses valuable runtime behavior: it fans out across two external services, partial failures degrade gracefully, and the first bundlephobia measurement can take 5-30s with a sources_failed field to indicate timeouts. This is more than the annotations alone provide, covering latency and partial success scenarios. It stops short of mentioning potential rate limits or authentication needs, but the additional context is strong.

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 information-dense and front-loaded with the core purpose, followed by usage, return format, ecosystem scope, and caveats. It is longer than the two-sentence ideal, but every sentence contributes distinct, non-redundant value, such as the timing note and failure handling. It earns a solid 4 for structure and economy.

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?

With no output schema, the description fully covers return values by naming the summary block fields, per-advisory details, links, and alternative versions. It also addresses ecosystem limitations and error behavior (bundlephobia timeout, sources_failed). Combined with the existing annotations and input schema, this gives an agent complete context to select and invoke the tool correctly.

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 input schema already has 100% description coverage for both parameters, including scoped package support and defaulting behavior. The tool description does not add any new parameter meaning beyond what the schema states; it simply references the concept of checking a package and version. Given the high schema coverage, 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, action-oriented phrase: 'Composite "should I add this npm package to my project" check in ONE call'. It clearly states the tool checks npm packages across deps.dev and bundlephobia, and it distinguishes itself from sibling research tools by focusing on npm package viability. The returned fields are enumerated, making the tool's scope unmistakable.

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 triggers are given: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also provides an exclusion boundary: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly,' directing users to an alternative for non-NPM ecosystems. This is clear when-to-use versus when-not-to-use guidance.

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