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

The description discloses behavior beyond the annotations: it's a composite of deps.dev and bundlephobia, handles partial failures gracefully, notes that the first bundlephobia measurement can take 5-30s, and mentions the sources_failed field. These runtime behaviors are not evident from the readOnly/idempotent hints.

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 five dense sentences, each earning its place: purpose, use cases, output structure, ecosystem limitation, and failure behavior. It front-loads the core purpose and avoids filler. Despite length, it remains well-structured and information-dense for a complex 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?

With no output schema, the description compensates by enumerating return fields (summary block with is_latest, license, advisory_count, bundle sizes, etc.), per-advisory details, links, and alternative versions. It also covers ecosystem scope and partial failure behavior, giving an agent everything needed to invoke and interpret results correctly.

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%: both 'package' and 'version' are described in the schema. The description adds no new parameter-level details; it only restates that 'package' is an npm package name and 'version' defaults to latest. Since the schema already provides full parameter semantics, a baseline score of 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 states a specific composite check for 'should I add this npm package to my project', listing concrete data points (license, advisories, bundle size). It clearly distinguishes itself from sibling tools like scan_competitor_ai_presence by naming its specific domain (npm dependencies) and the output format.

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?

Provides explicit triggers: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. It also gives an exclusion—'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly'—and names the alternative. This is clear when-to-use and when-not-to-use guidance.

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