prep

To clean up AI-generated code before committing, you run a multi-stage pipeline that removes AI artifacts, simplifies logic, executes linting and type checks, and performs a final review to ensure quality and readiness.

The best way to remove dead code and unused exports is using an automated cleanup pipeline that identifies unused files and exports, deleting them to streamline your project before executing final code reviews.

Automated code review for commit preparation works by sequentially executing deslop, simplify, dead code removal, and lint/type checks, coordinating these stages to catch bugs and enforce project standards before you commit.

Yes, you can fix linting and type errors automatically when polishing AI code by running a multi-stage cleanup pipeline that enforces project standards and addresses type checking as part of its sequential review process.

You do not need any specific external dependencies to run this code cleanup and review pipeline, as it coordinates its own sequential execution of deslop, simplify, knip, lint/type checks, and code-review skills internally.