dev_npm

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

No annotations are provided, so the description carries the full burden. It discloses cost ($0.003/call), caching (1 hour), and specifics of returned data (latest version, dist-tags, deprecation message, etc.). This provides good insight into behavior beyond mere functionality.

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 concise with two paragraphs. It front-loads the cost and purpose, then details. Every sentence adds value—no fluff. Well-structured for quick comprehension.

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 and no annotations, the description thoroughly explains what data the tool returns, including version details, deprecation status, and popularity metrics. It also covers caching and cost, making the tool's behavior fully transparent.

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 coverage is 100%, so baseline is 3. The description adds extra guidance for URL-encoding scoped package names, which adds value beyond the schema's description. The cost and caching info also help understand parameter usage context.

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 checks npm package version freshness, deprecation, and popularity. It uses a specific verb and resource, and the domain (npm) distinguishes it from sibling tools like dev_pypi.

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 lists use cases (dependency auditing, supply-chain security, etc.) and provides encoding guidance for scoped packages. While it doesn't explicitly mention when not to use, the sibling tools are from different domains, making the context clear.

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