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

Beyond the annotations that already indicate safety and idempotency, the description adds critical behavioral details: composite fan-out, partial failures degrade gracefully, bundlephobia's first measurement can take 5-30s, and sources_failed will list timeouts. 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 well-structured with key information front-loaded (composite nature, use cases). It is relatively long but every sentence adds necessary detail. Could be slightly more concise but still 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?

Despite the absence of an output schema, the description thoroughly details the return value (summary block, per-advisory detail, links, alternative versions) and handles edge cases like partial failures, timeouts, and ecosystem limitations. 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?

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining that scoped packages are accepted and clarifying the default behavior for version, which raises the score slightly above baseline.

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 that the tool performs a composite check for npm packages, combining data from deps.dev and bundlephobia. It explicitly differentiates from sibling tools by specifying it's for npm only and mentions alternatives for other ecosystems.

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 provides explicit and actionable usage guidance: 'Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me".' It also clarifies when not to use (other ecosystems) and names the alternative tool.

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