lookup_npm_package

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

With no annotations, the description carries the burden. It discloses the nature of the tool (read-only, returns signals) and mentions supply chain attack relevance, publisher depth, and behavioral signals. It does not describe rate limits or API dependencies, but for a simple lookup tool, the transparency is sufficient.

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: 4 sentences plus bullet-point use cases and examples. It front-loads the purpose, details outputs, then provides context and examples. Every sentence is informative and earns its place.

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 one parameter and no output schema, the description explains the return values (signals list) and usage scenarios. It covers input semantics well, though lacks potential notes on data freshness or API limitations. Overall, it is adequately complete for a straightforward 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?

The single parameter 'package' has a schema description covering 100%. The description adds value by specifying scoped packages need '@' prefix and giving examples, which aids correct input. This exceeds the baseline of 3 for full schema coverage.

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 identifies the tool as retrieving a 'behavioral commitment profile' for npm packages, listing specific signals (package age, download volume, trend, etc.). It distinguishes from siblings like lookup_pypi_package and lookup_github_repo by focusing on npm packages, making the purpose precise and unambiguous.

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 states use cases ('vetting dependencies, identifying abandonware, due diligence') and provides examples. It does not mention when not to use it or name alternative tools, but the context signals and sibling list imply differentiation. The guidance is strong but lacks explicit exclusions.

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