lidarr_review_setup

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

No annotations are provided, so the description carries the burden. It states 'Returns all settings', implying a read-only operation, but does not explicitly confirm safety or other behaviors like rate limits. More details would be beneficial.

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?

Two sentences, front-loaded with purpose and content list. No wasted words; every sentence 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?

With zero parameters and no output schema, the description is sufficient. It covers what the tool returns and its intended use case, leaving no critical gaps.

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 has no parameters (100% coverage trivially), but the description adds value by explaining the output content. Baseline 3 is adjusted up because the description enriches understanding beyond the empty 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?

Description clearly states it returns a comprehensive configuration review for Lidarr, listing specific categories (quality profiles, download clients, etc.). The verb 'Get' combined with 'comprehensive configuration review' differentiates it from sibling tools that return individual settings.

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?

Explicitly states 'Use this to analyze the setup and suggest improvements', which guides the agent on when to use it. While it doesn't exclude other tools, the context of sibling tools (e.g., lidarr_get_health) implies this is for holistic analysis.

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