What problem does it solve?
Legacy codebases accumulate inconsistent naming, formatting, and file organization over time, making them harder to read and riskier for AI agents to modify. This Skill detects the dominant style already practiced in a project and applies it consistently, without ever altering behavior.
Core Features & Use Cases
- Pattern Detection: Analyzes the existing code to discover the dominant conventions (naming, indentation, import order, comment style) instead of imposing a foreign style; if no clear pattern exists, it asks the user to declare the target standard.
- Gated Batch Application: Groups inconsistencies into cohesive batches and shows a diff for each one, applying changes only after explicit user approval.
- Safe Renaming: Treats renames as reference-sensitive operations, scanning all usages or using language tooling for safe renames, and runs the test suite afterward as proof that semantics are unchanged.
- Use Case: After running the reversa-refactor workflow on a legacy module, use this Skill to normalize variable naming and import ordering across the touched files, reviewing each diff batch before it lands.
Quick Start
Ask the agent to run /reversa-standardize on a target file or folder so it detects the project's dominant style and proposes gated diff batches for approval.
