What problem does it solve? AI agents generate code at high speed, and without disciplined version control, changes become unreviewable, hard to revert, and risky to merge. This Skill enforces structured git practices so every change is atomic, traceable, and reversible. ## Core Features & Use Cases - Atomic Commit Discipline: Enforces small, single-purpose commits with conventional message types (feat, fix, refactor, test, docs, chore) that explain the why behind each change. - Trunk-Based Branching Strategy: Guides short-lived feature branches, consistent branch naming, and git worktrees for running parallel AI agent work in isolated directories. - Pre-Commit Hygiene & Debugging: Provides checklists for staged diff review, secret scanning, tests, and linting, plus git bisect, blame, and log techniques for debugging. - Use Case: An AI agent implements a feature across multiple files. Instead of one giant commit, it commits each tested slice with a descriptive message, producing a clean history that reviewers can follow and revert if needed. ## Quick Start Use the git-workflow-and-versioning skill to commit my current changes as atomic commits with proper messages.