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

Annotations already mark it as read-only, open-world, idempotent, non-destructive. The description adds depth: it fans out across two external APIs, returns specific fields (is_latest, license, advisory_count, bundle sizes, dependency_count, has_esm, tree_shakeable), and explains graceful degradation (sources_failed lists timeouts). No contradiction.

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-structured: first sentence is the hook, followed by return fields, ecosystem scope, and failure behavior. At ~100 words, every sentence earns its place, though it could be slightly shorter.

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?

For a composite tool with no output schema, the description fully specifies return structure (summary block, per-advisory detail, links, alternative versions) and edge cases (scoped packages, version default, partial failures, timing). No gaps remain.

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 is 3. The description adds value by clarifying that scoped packages are accepted and that version defaults to latest when omitted—information not in parameter descriptions.

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 starts with a clear verb-resource pair ('should I add this npm package'), immediately conveying a composite check combining deps.dev (license, advisories, version history) and bundlephobia (size, dependencies, ESM). This specificity distinguishes it from sibling tools like 'validate_claim' or 'deep_research'.

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 'Use whenever an agent asks "is X safe / popular / small"' and gives alternatives for non-NPM ecosystems ('PyPI / Maven / Cargo / Go fall under deps.dev:version directly'). Also warns about partial failures and timing (5-30s for new versions).

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