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

Annotations already mark the tool as read-only and idempotent. The description goes beyond by detailing the composite nature, external service calls, potential latency (5-30s for first measurement), graceful degradation, and the sources_failed field. 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 a single, dense paragraph that front-loads the main purpose. Every sentence adds value, covering purpose, usage, limitations, return structure, and failure behavior. Slightly long but well-organized for the complexity.

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 thoroughly covers return values: summary fields, advisory details, links, and alternatives. It also explains failure modes and ecosystem limitations. Highly complete for a composite tool with external dependencies.

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 parameters. The description adds minimal new information (scoped packages, default to latest version), which is already in the schema descriptions. Baseline 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 clearly states the tool is a composite check for npm packages, integrating deps.dev and bundlephobia. It specifies the exact purpose: evaluating safety, popularity, and size. This distinguishes it from siblings like validate_claim or ask_pipeworx, which are unrelated.

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 explicitly says 'Use whenever an agent asks "is X safe / popular / small"' and notes the NPM-only limitation, suggesting alternatives for other ecosystems. It lacks an explicit 'when not to use' but provides enough context for appropriate usage.

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