analyze_code_quality

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'analyze' suggests a read-only operation, it doesn't explicitly state whether this requires authentication, has rate limits, returns structured data, or involves computational costs. The mention of 'detailed metrics' hints at output format but remains vague about actual behavior beyond the basic function.

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 a single, efficient sentence that front-loads the core purpose. There's no wasted text or redundancy. However, it could be slightly more structured by separating the analysis function from the output description, but it remains appropriately concise for a tool with clear parameters.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details about output format, error conditions, or integration with sibling tools. For a code analysis tool that likely returns complex metrics, more context about the nature of 'suggestions' and 'detailed metrics' would be helpful.

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 description adds no parameter-specific information beyond what's already in the schema (which has 100% coverage). It doesn't explain what 'rules' might entail, how 'language' affects analysis, or what format 'code' should be in. Since the schema descriptions adequately cover the parameters, the baseline score of 3 is appropriate, but no extra value is added.

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: 'Analyze code quality and provide suggestions with detailed metrics'. It specifies the verb ('analyze'), resource ('code quality'), and output type ('suggestions with detailed metrics'). However, it doesn't differentiate from sibling tools like 'analyze_files_batch' or 'get_language_rules', which prevents 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 no guidance on when to use this tool versus alternatives. With siblings like 'analyze_files_batch' (for batch analysis) and 'get_language_rules' (for rule retrieval), there's no indication of when this single-code analysis tool is preferred or what its limitations might be. The description only states what it does, not when to use it.

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