addyosmani/agent-skills/git-workflow-and-versioning
- community
- ext:[{"type":"hook","description":"Pre/post lifecycle hooks"}]
Checking that the SKILL.md file is still in the repository.
Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, splitting uncommitted work in a messy working tree into clean atomic commits, opening or reviewing a pull request (PR), pushing to a remote, or when you need to organize work across multiple parallel streams. Use when cutting a release, choosing a semantic version bump, tagging, or writing a changelog.
Install
npx vskill@latest install addyosmani/agent-skills/git-workflow-and-versioningSemi-extensibleMentions customization, but needs skill-specific knowledge. Read the extensible skills standard
SKILL.md
Git Workflow and Versioning
Overview
Git is your safety net. Treat commits as save points, branches as sandboxes, and history as documentation. With AI agents generating code at high speed, disciplined version control is the mechanism that keeps changes manageable, reviewable, and reversible.
When to Use
Always. Every code change flows through git.
Core Principles
Trunk-Based Development (Recommended)
Keep main always deployable. Work in short-lived feature branches that merge back within 1-3 days. Long-lived development branches are hidden costs — they diverge, create merge conflicts, and delay integration. DORA research consistently shows trunk-based development correlates with high-performing engineering teams.
This is the recommended default. Teams using gitflow or long-lived branches can adapt the principles (atomic commits, small changes, descriptive messages) to their branching model — the commit discipline matters more than the specific branching strategy.
- Dev branches are costs. Every day a branch lives, it accumulates merge risk.
- Release branches are acceptable. When you need to stabilize a release while main moves forward.
- Feature flags > long branches. Prefer deploying incomplete work behind flags rather than keeping it on a branch for weeks.
1. Commit Early, Commit Often
Each successful increment gets its own commit. Don't accumulate large uncommitted changes.
Commits are save points. If the next change breaks something, you can revert to the last known-good state instantly.
2. Atomic Commits
Each commit does one logical thing:
3. Descriptive Messages
Commit messages explain the why, not just the what:
Format:
Types:
feat— New featurefix— Bug fixrefactor— Code change that neither fixes a bug nor adds a featuretest— Adding or updating testsdocs— Documentation onlychore— Tooling, dependencies, config
4. Keep Concerns Separate
Don't combine formatting changes with behavior changes. Don't combine refactors with features. Each type of change should be a separate commit — and ideally a separate PR:
Separate refactoring from feature work. A refactoring change and a feature change are two different changes — submit them separately. This makes each change easier to review, revert, and understand in history. Small cleanups (renaming a variable) can be included in a feature commit at reviewer discretion.
5. Size Your Changes
Target ~100 lines per commit/PR. Changes over ~1000 lines should be split. See the splitting strategies in code-review-and-quality for how to break down large changes.
Branching Strategy
Feature Branches
- Branch from
main(or the team's default branch) - Keep branches short-lived (merge within 1-3 days) — long-lived branches are hidden costs
- Delete branches after merge
- Prefer feature flags over long-lived branches for incomplete features
Branch Naming
Working with Worktrees
For parallel AI agent work, use git worktrees to run multiple branches simultaneously:
Benefits:
- Multiple agents can work on different features simultaneously
- No branch switching needed (each directory has its own branch)
- If one experiment fails, delete the worktree — nothing is lost
- Changes are isolated until explicitly merged
The Save Point Pattern
This pattern means you never lose more than one increment of work. If an agent goes off the rails, git reset --hard HEAD takes you back to the last successful state.
Change Summaries
After any modification, provide a structured summary. This makes review easier, documents scope discipline, and surfaces unintended changes:
This pattern catches wrong assumptions early and gives reviewers a clear map of the change. The "DIDN'T TOUCH" section is especially important — it shows you exercised scope discipline and didn't go on an unsolicited renovation.
Pre-Commit Hygiene
Before every commit:
Automate this with git hooks:
Handling Generated Files
- Commit generated files only if the project expects them (e.g.,
package-lock.json, Prisma migrations) - Don't commit build output (
dist/,.next/), environment files (.env), or IDE config (.vscode/settings.jsonunless shared) - Have a `.gitignore` that covers:
node_modules/,dist/,.env,.env.local,*.pem
Using Git for Debugging
Release & Versioning
Commits are how you track change; a version is how your consumers track it. The moment anything else depends on your code — another team, a published package, a deployed client — "latest on main" stops being a sufficient answer to "what am I running, and is it safe to upgrade?" A version number and a changelog are the contract that answers it.
Semantic Versioning
For anything with consumers, version MAJOR.MINOR.PATCH and let the number carry meaning:
The number is a promise, so make the code match it. A "patch" that changes behavior consumers relied on is a major change wearing a disguise (Hyrum's Law — see the api-and-interface-design skill). When unsure whether a change is breaking, assume it is; a surprise major is far cheaper than a broken consumer.
Tag the release, and let the tag be the source of truth
A release is an immutable point in history, not a moving branch. Tag it so it can always be reproduced:
Derive the version from the tag rather than hand-editing it in scattered files, so the artifact, the tag, and the changelog can never disagree.
Keep a changelog written for humans
A changelog is not git log. It's the curated, consumer-facing answer to "what changed and do I care?" — grouped by Added / Changed / Fixed / Deprecated / Removed / Security, newest on top, every entry phrased around user impact, not internal mechanics.
Write the entry in the same change that makes the change, while the impact is fresh — not reconstructed from commit archaeology at release time. Breaking changes get a migration note and a deprecation window (follow the deprecation-and-migration skill); shipping the actual release is the shipping-and-launch skill's job — this section is the versioning contract that feeds it.
Common Rationalizations
This is the start of the file. Read the full SKILL.md on GitHub.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/git-workflow-and-versioning/SKILL.md
Popularity
- Repository stars
- 151
- Repository forks
- 9
- 7-day trend score
- 25
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 30 Mar 2026, 7 months ago.
Extension points
hookPre/post lifecycle hooks
Works with
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