apply_codemod

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

The description adds substantial behavioral context beyond annotations: it explains the two-step dry-run workflow, notes the tool is 'potentially destructive' (matching destructiveHint=true), and details the return format. No contradictions with annotations.

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 (4 sentences) and efficiently front-loads the core purpose. Each sentence adds essential information: purpose, workflow, usage examples, and warnings. No unnecessary words.

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 7 parameters and no output schema, the description covers the workflow, return format, and safety warnings. It mentions the confirm_large trigger. It could be more thorough on edge cases or explicit parameter constraints, but the essentials are present.

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 clear descriptions. The description adds value by explaining the dry-run workflow and how parameters interact (e.g., confirm_large for >20 files). It integrates parameter usage into the overall process, enhancing understanding 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 the tool's purpose: 'Bulk regex find-and-replace across files.' It specifies the verb (find-and-replace) and resource (files), and distinguishes it from siblings like apply_move and apply_rename by emphasizing regex and multiple files.

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 specific use cases ('mechanical changes like adding async/await, renaming patterns, updating imports') and instructs to 'Always preview with dry_run=true first.' It does not explicitly list when not to use or alternative tools, but the context is sufficient for appropriate use.

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