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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses multi-source fan-out behavior, graceful degradation on partial failures ("sources_failed will list it if it times out, the rest still returns"), and a notable latency caveat ("bundlephobia's first measurement on a new version can take 5-30s"). This significantly enriches the annotation data without 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 every sentence earns its place: purpose, usage, return value, ecosystem limits, and failure behavior. It is front-loaded with the core purpose, uses compact lists and parentheticals, and avoids filler. Appropriate length for a composite tool.

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?

Despite lacking an output schema, the description thoroughly explains the return structure (summary block fields, per-advisory detail, links, alternatives) and behavioral edge cases (NPM-only, timeout handling). For a multi-source composite tool with partial failures and latency, this is a complete and actionable description.

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 description coverage is 100%, with both 'package' and 'version' already well-documented in the schema. The description adds minor context (e.g., scoped packages accepted, version defaults to latest) but does not materially enhance parameter meaning beyond what the schema states. Baseline 3 is appropriate as the schema carries the load.

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 opens with a specific, composite purpose: "Composite 'should I add this npm package to my project' check in ONE call" and lists concrete data sources (deps.dev, bundlephobia) and checks (license, advisories, bundle size, etc.). It clearly distinguishes from siblings by emphasizing the compound nature and NPM scope, avoiding ambiguity with tools like scan_competitor_ai_presence.

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?

Explicit usage triggers are given: "Use whenever an agent asks 'is X safe / popular / small' or 'what does adding lodash cost me'". It also provides exclusions and alternatives: "NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly", directing agents to the correct tool 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.