audit_library

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

No annotations are provided, so the description fully carries the burden. It discloses output format (JSONL), return values (file path, summary stats), and conditional behavior for libraryRoot parameter (source-level evidence vs unknown). However, it does not explicitly state whether the operation is read-only or has side effects.

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 three short sentences. It front-loads the core purpose and output format without unnecessary words. Every sentence adds value.

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?

For a tool with three optional parameters and no output schema, the description adequately covers key behaviors and return values. However, it lacks detail on what 'summary stats' include, which could be clarified.

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% with descriptions for all three parameters. The description adds value by explaining the optional outputPath, default libraryId, and the behavioral difference when libraryRoot is provided (source-level a11y evidence). This goes beyond the schema.

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 it generates a JSONL audit report scoring every component across all dimensions. It uses specific verbs and identifies the resource (library) and output format, distinguishing it from sibling tools that focus on individual checks.

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 implies usage for full library auditing but does not explicitly state when to use this tool versus specific check tools (e.g., check_color_contrast). No when-not-to-use or alternative guidance is provided.

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