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

The description adds behavioral traits beyond annotations, such as partial failure handling with timeout details (bundlephobia can take 5-30s), graceful degradation with sources_failed, and the fact that it fans out across multiple sources. No contradiction with 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 comprehensive but not overly verbose; it packs useful information into a few sentences. It is front-loaded with the core purpose and organized logically. A minor reduction in length could improve conciseness, but the structure is effective.

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, lack of output schema, and 100% schema coverage, the description provides a complete picture: explains return values (summary block, per-advisory detail, links, alternative versions), handles failure scenarios, and defines ecosystem boundaries. No gaps remain.

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?

The input schema covers both parameters with descriptions, achieving 100% coverage. The description adds value by clarifying that scoped packages are accepted and that the version defaults to the latest when omitted, enhancing clarity beyond 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 states a specific verb+resource ('scan dependency') and clearly defines it as a composite check for npm packages, covering safety, size, and popularity. It distinguishes from sibling tools by specifying ecosystem scope and the underlying external sources (deps.dev, bundlephobia).

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 guidance is provided: 'Use whenever an agent asks 'is X safe / popular / small' or 'what does adding lodash cost me.' It also explicitly excludes other ecosystems ('PyPI / Maven / Cargo / Go fall under deps.dev:version directly').

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