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

Annotations already declare this read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond that: data is fetched 'straight from each registry', supplementary download counts come from npm and pypistats, and deprecated or stale packages are flagged. It does not contradict the 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 compact and front-loaded: it starts with the package types and core output fields, then adds data-source and pricing context. The list of fields is long but every element carries relevant information; there is no filler.

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?

Since there is no output schema, the description carries the burden of describing the return surface, and it does so by listing the key fields and edge-case flags. It omits failure or not-found behavior, but for a simple two-parameter tool with openWorldHint, the remaining gap is minor.

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?

With 0% schema description coverage, the description must compensate. It effectively defines the ecosystem parameter by listing npm, PyPI, and crates.io, and clarifies that the 'name' parameter refers to an installable package. It does not explicitly mention the npm default or format requirements, but the schema already provides those details.

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 names a concrete resource ('Any npm, PyPI or crates.io package') and enumerates the exact data returned: latest version, release date, license, downloads, maintainers, repo, dependency count, and deprecation status. It also states the intended use case ('to pick or vet a dependency'), which clearly separates it from siblings like github_repo or arxiv_search.

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?

The description gives clear context for when to use this tool: dependency selection or vetting. It does not explicitly name alternative tools or state when not to use it, so it falls short of the strongest possible guidance.

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