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

The description discloses rich behavioral traits beyond annotations: it fans out to multiple sources, can take 5-30s on first bundlephobia measurement, degrades gracefully on partial failures, and lists the `sources_failed` field. It also details the return structure, which is especially valuable given no output schema. No contradiction with readOnlyHint/idempotentHint.

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. It front-loads the core purpose, then provides usage, return fields, limitations, and failure behavior. It is well-structured with a natural flow and no redundant fluff, given the tool's composite nature.

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 listing the summary fields and other return components. It covers when to use, what data is aggregated, ecosystem limitations, latency expectations, and graceful degradation. This is complete enough for an agent to correctly invoke and interpret the tool.

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%: both `package` and `version` have clear descriptions including scoped packages and default-to-latest. The tool description adds little beyond the schema; it reinforces the npm-only constraint but does not offer new parameter-level detail. Baseline 3 applies.

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 check for evaluating whether to add an npm package to a project, combining deps.dev and bundlephobia data. It uses a specific verb ('scan') and resource ('dependency'), and is easily distinguished from sibling tools like scan_competitor_ai_presence or bet_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?

Explicit usage guidance is provided: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me"'. It also gives an exclusion and alternative: 'NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly', clarifying when not to use this tool.

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