find_dead_code

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

Annotations indicate destructiveHint: true, readOnlyHint: false, openWorldHint: true, and idempotentHint: false, suggesting this tool performs mutable, non-idempotent operations with potential side effects. The description adds value by specifying the analysis method ('CFG analysis'), but it doesn't elaborate on what 'destructive' entails (e.g., modifies files, generates reports) or other behavioral traits like rate limits or authentication needs. With annotations covering key aspects, the description provides some context but lacks depth.

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: 'Find unreachable code using Control Flow Graph (CFG) analysis'. It is front-loaded with the core purpose and method, with no unnecessary words or redundancy. Every part of the sentence contributes directly to understanding the tool's function, making it highly concise and well-structured.

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 has annotations (including destructiveHint: true) but no output schema, the description is moderately complete. It specifies the analysis method ('CFG analysis'), which adds context beyond the annotations. However, it doesn't explain the output format, potential side effects from the destructive hint, or how results are returned, leaving gaps that could hinder an AI agent's understanding of the full tool behavior.

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 clear descriptions for both parameters: 'min_severity' (minimum severity level with default) and 'path' (path to Python code). The description doesn't add any semantic details beyond the schema, such as explaining how 'CFG analysis' interacts with these parameters or providing examples. Given the high schema coverage, a baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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: 'Find unreachable code using Control Flow Graph (CFG) analysis'. It specifies the verb ('Find'), resource ('unreachable code'), and method ('CFG analysis'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'analyze_code' or 'detect_clones', which might also analyze code structure, so it misses the highest 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. It doesn't mention any prerequisites, exclusions, or comparisons to sibling tools such as 'check_complexity' or 'detect_clones'. Without this context, an AI agent might struggle to choose this tool appropriately in a multi-tool environment.

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