Dependency Score Tool

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

The annotations indicate readOnlyHint=true, which the description aligns with by describing a scanning/checking operation rather than a mutation. The description adds behavioral context beyond annotations: it specifies that 'unknown' should be used for version if not known, advises on handling low scores (stop and ask user), and emphasizes checking imports beyond manifest files. However, it doesn't detail rate limits, authentication needs, or specific return formats, leaving some behavioral aspects uncovered.

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 appropriately sized at four sentences, with the first sentence front-loading the core purpose. Each sentence adds value: purpose, parameter guidance, usage context, and procedural advice. There's no redundant information, though the structure could be slightly more streamlined by integrating the 'unknown' version note with the parameter semantics more cohesively.

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 (dependency scoring with quality/security focus), the description provides good contextual completeness. It covers purpose, usage scenarios, procedural steps, and parameter hints. With annotations covering read-only safety and no output schema, the description doesn't need to explain return values but could benefit from more detail on score interpretation or error handling. It's largely complete but has minor gaps for a tool of this nature.

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 schema fully documents the parameters (packages array with ecosystem, depname, version, and optional platform). The description adds minimal parameter semantics: it reiterates using 'unknown' for version if not known, which is already in the schema's default/description. It doesn't provide additional meaning beyond the schema, such as explaining the scoring implications of different ecosystems or platforms, so it meets the baseline for high 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 states the tool's purpose: 'Get the dependency score of packages' and specifies it's for 'scanning dependencies for their quality and security.' It identifies the resource (packages) and the action (get/scan scores). However, with no sibling tools mentioned, there's no explicit differentiation from alternatives, preventing a perfect score.

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 clear usage context: 'Use this tool to scan dependencies for their quality and security on existing code or when code is generated.' It also offers procedural guidance: 'Stop generating code and ask the user how to proceed when any of the scores are low' and 'check the imports in the code, not just the manifest files.' This gives strong contextual direction, though it doesn't explicitly mention when not to use it or name alternatives (none are listed as siblings).

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