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

Annotations already declare readOnlyHint and idempotentHint, but the description adds valuable behavioral details: it is a composite call that fans out across two services, partial failures degrade gracefully, and bundlephobia's first measurement can take 5-30s with sources_failed listing timeouts. This goes beyond what annotations provide, making failure modes transparent.

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 relatively long but every sentence serves a purpose: purpose, usage triggers, output details, ecosystem scope, and failure behavior are all packed in. It is front-loaded with the core value proposition and then expands into necessary operational details. Slightly dense but not wasteful.

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 (composite of two external services) and the absence of an output schema, the description does an excellent job of explaining the return values (summary block with specific fields, per-advisory detail, links, alternative versions) and edge cases (partial failures, latency, non-npm ecosystems). This makes the tool fully understandable without further documentation.

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%, so both parameters (package, version) are already well-documented in the schema. The description adds no extra parameter-level detail beyond what the schema states, but it does elaborate on output semantics, which is relevant for understanding what the tool returns. Since schema carries the parameter burden, a baseline 3 is appropriate.

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 purpose: a composite 'should I add this npm package' check that fans out to deps.dev and bundlephobia. It lists specific output fields (license, advisories, bundle size, etc.) and differentiates from sibling tools like scan_competitor_ai_presence by focusing on package evaluation for npm projects.

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 explicitly says to use it 'whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. It also provides an exclusion: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly', effectively naming an alternative path for non-npm ecosystems.

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