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

The description discloses failure behavior ('Partial failures degrade gracefully'), timing caveats (5-30s for first bundlephobia measurement), and the sources_failed field for timeouts. It also details what the return block contains, which is beyond the readOnlyHint and idempotentHint annotations.

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 each sentence serves a purpose: it defines the composite check, gives usage triggers, specifies return structure, outlines ecosystem scope, and explains partial failure behavior. It is front-loaded with the core purpose and uses clear punctuation to separate sections.

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?

Since there is no output schema, the description compensates by specifying the exact return summary fields and per-advisory details. It also covers limitations (only NPM, bundlephobia timing) and fallback behavior, making it sufficiently complete for an agent to know what to expect.

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% for both package and version. The description adds no substantial new meaning beyond the schema; it merely reaffirms that package is a npm package name and version defaults to latest, both already in the schema.

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 'should I add this npm package to my project' check that aggregates data from deps.dev and bundlephobia. The resource (npm package) and scope (NPM ecosystem) are explicit, and it distinguishes itself from siblings like scan_competitor_ai_presence by specifying exactly what it evaluates.

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 provides when to use: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also tells agents when NOT to use it by stating 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly,' which directs them to an alternative tool.

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