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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the tool's safety profile is clear. The description adds detail about the returned metrics but does not reveal additional behavioral traits such as rate limits, authorization needs, or data freshness.

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 concise and well-structured. It starts with a clear summary sentence, then details the metrics, arguments, return structure, and examples. Every section provides necessary information without unnecessary fluff.

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 no output schema, the description thoroughly explains the return value with a breakdown of scores and metrics. It also includes examples. For a simple one-parameter tool, this provides complete context for an agent to understand inputs and outputs.

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 100% schema description coverage, the schema already documents the single parameter. The description reinforces its purpose (the npm package name) and ties it to the tool's functionality, but does not add new constraints or format details beyond what the schema provides.

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 gets quality, popularity, and maintenance scores for an npm package from npms.io. It lists specific metric categories and provides examples, distinguishing it from siblings like npm_package_info which would focus on general details.

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 explains what the tool provides (scores, metrics) but does not explicitly state when to use it over alternatives like npm_package_info or npm_search. The examples imply it's for comprehensive scoring, but no direct comparison or exclusion criteria are given.

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