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

Annotations already mark readOnlyHint=true and idempotentHint=true, and the description adds behavioral context about graceful degradation ('Partial failures degrade gracefully'), potential latency ('bundlephobia's first measurement on a new version can take 5-30s'), and how failures are reported ('sources_failed will list it if it times out'). This exceeds the safety profile given by annotations.

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-organized, front-loading the core purpose in the first sentence, then providing usage, output, and failure info without redundancy. Each sentence adds new, actionable information for the agent.

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 composite nature and lack of an output schema, the description fully accounts for return values (summary block fields, per-advisory detail, links, alternative versions), ecosystem limitations, and failure modes. No critical context appears missing.

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 already documents both parameters with 100% coverage, including scoped package support and default version behavior. The description does not add additional parameter-level detail beyond restating what the schema provides, so baseline 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 clearly identifies it as a composite check for deciding whether to add an npm package, listing both data sources (deps.dev, bundlephobia) and output fields. This distinguishes it from sibling research tools by its specific npm/package scope and composite nature.

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 when-not-to-use and alternative: 'PyPI / Maven / Cargo / Go fall under deps.dev:version directly', giving clear exclusion criteria.

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