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

Beyond annotations (readOnly, idempotent), the description discloses important behaviors: partial failures degrade gracefully, bundlephobia first measurement can take 5-30s, sources_failed lists timeouts, and the rest still returns. Output structure is detailed.

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: purpose first, then detailed breakdown of functionality, usage, and behavior. Every sentence adds necessary information without redundancy.

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 (multisource, partial failures, no output schema), the description covers all necessary context: what it returns, behavior on errors, and limitations. It is fully self-contained.

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 coverage is 100% with good descriptions. The description adds value by mentioning that scoped packages are accepted and that version defaults to latest when omitted.

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 specific purpose: a composite 'should I add this npm package' check combining data from deps.dev and bundlephobia. It distinguishes itself from siblings by focusing on npm dependency analysis.

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 mentions when to use: when an agent asks about safety, popularity, size, or cost of adding a package. Also specifies limitations (NPM only in v1, fallback for other ecosystems) and alternative tools for non-NPM packages.

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