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

Description adds significant behavioral context beyond annotations: fans out to external services, partial failures degrade gracefully, bundlephobia first measurement can take 5-30s, and sources_failed list. Aligns with annotations (readOnly, idempotent, openWorld).

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?

Description is detailed but well-structured, front-loading purpose and breaking down capabilities. Some redundancy (e.g., mentions npm ecosystem twice) but overall concise for the complexity.

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, description fully covers return data (summary block, per-advisory detail, links, alternatives) and behavior (partial failures, timing). Sufficient for agent to understand expected output and edge cases.

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%, so baseline 3. Description does not add meaning beyond schema: 'package' is npm package name, 'version' defaults to latest. No additional semantics provided.

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 it is a composite check for npm packages using deps.dev and bundlephobia, addressing questions about safety, popularity, and size. It distinguishes from sibling tools, which are unrelated (e.g., AI visibility, poly market).

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: when an agent asks about safety, popularity, size, or cost of adding an npm package. Notes NPM ecosystem limitation and fallback for other ecosystems. Lacks explicit when-not-to-use but provides clear context.

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