suggest_refactoring

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It implies a read-only analysis by saying 'provide recommendations,' but it does not explicitly state that the tool does not modify files, how results are returned, or any requirements or side effects. This is a significant gap for a tool whose behavior is otherwise opaque.

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 short sentence and is easy to scan. 'AI-powered' is filler that doesn't add operational value, but otherwise the text is free of redundancy. It is concise but so terse that it sacrifices useful detail.

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?

The tool has five parameters, no output schema, and no annotations, so the description should explain return values, side effects, and how parameters influence results. It only states that it provides refactoring recommendations, leaving an agent without enough context to confidently invoke it. Sibling tools are not referenced to help disambiguate.

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%, with detailed descriptions for all five parameters including enums, defaults, and constraints. The tool description adds no additional parameter meaning beyond what the schema already provides. Baseline 3 is appropriate because the schema carries the documentation burden.

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 uses a specific verb ('provide') and a clear resource ('refactoring recommendations'), which indicates the tool suggests code improvements. It is distinct from siblings like analyze_performance or detect_code_smells, though the distinction is not explicitly stated. 'AI-powered' is unnecessary but doesn't obscure the purpose.

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 gives no guidance on when to use this tool versus sibling tools such as detect_code_smells or analyze_performance. It also doesn't mention the focusArea or excludeTypes parameters that could help an agent tailor the call. An agent must infer usage solely from the tool name and schema.

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