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

Beyond the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false), the description discloses key behavioral aspects: the fan-out across two third-party services, graceful degradation on partial failures ('sources_failed will list it if it times out'), and the potential 5-30s delay for bundlephobia's first measurement on a new version. These details are not visible in the annotations and add significant operational context.

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 well-structured and front-loaded with the core purpose, followed by use cases, return value breakdown, ecosystem limitation, and failure behavior. Every sentence carries useful information, and the use of em dashes and semicolons keeps it readable despite its length. No filler or redundant content.

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 (composite of two sources) and the absence of an output schema, the description thoroughly explains what is returned (summary block fields, per-advisory detail, links, alternative versions) and handles edge cases (timeouts, partial failures, ecosystem support). It provides enough detail for an agent to understand the tool's scope, latency, and output without needing additional documentation.

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 describes both parameters (package and version) with 100% coverage, including scoped package acceptance and version default behavior. The description does not add new parameter-level semantics; it only implies version usage by mentioning 'latest published version' in the context, which is already stated in the schema. Hence, it meets the baseline for high schema coverage.

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 purpose as a composite 'should I add this npm package to my project' check, specifying the two data sources (deps.dev and bundlephobia) and the types of information gathered (license, advisories, version history, bundle size, dependency count, ESM/tree-shake). This distinguishes it from sibling tools like deep_research or bet_research, which serve 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?

Explicitly states when to use: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also provides an important exclusion: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly,' which guides users away from this tool for other ecosystems. However, it doesn't mention alternative sibling tools by name, so it doesn't fully cover when not to use relative to all siblings.

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