AI Prompts for Git Commit Messages

Before: The Weak Prompt

Picture this: you're a tech lead reviewing a PR from a new developer. The code is fine. The commit history looks like this:

• fix stuff

  Copy

• update

  Copy

• wip

  Copy

• final

  Copy

• final2

  Copy

• actually final

  Copy

• hotfix

  Copy

You've seen this before. Maybe you've written commits like this. The code ships. Six months later, a bug appears in exactly the feature area this PR touched. You

git log

git blame

update

This is the cost of bad commit messages — not now, but later. And "write me a commit message" is one of the most commonly underpowered AI prompts in a developer's toolkit.

Why It Fails

The minimal commit message prompt:

Write a git commit message for these changes.

[paste diff or description]

The AI writes something like: "Update user authentication logic." Grammatically correct. Technically accurate. Almost useless for future debugging.

Three things the output never includes unless prompted:

The why. Every change was made for a reason. The commit message should capture the reason, not just describe what changed. Future-you reading this commit in a blame trace doesn't need to know that the authentication logic was updated — the diff shows that. Future-you needs to know why.

The problem that was solved. A good commit message answers "what was broken or suboptimal before this?" That context makes the change legible without reading every line of code.

The trade-offs or alternatives considered. For non-trivial changes, "I chose approach A over approach B because..." is the institutional knowledge that lives in commit messages or doesn't live anywhere.

⚠️ Common mistake: Treating commit messages as code descriptions rather than change narratives. Code describes what the system does. Commit messages describe what changed about the system, why, and what the effect should be.

After: The Improved Prompt

Write a git commit message in the Conventional Commits format for the following change.

What changed (code-level): [describe the technical change]
Why this change was needed: [describe the problem or requirement]
Effect on users or system: [what will be different after this change]
Anything considered and rejected: [optional: other approaches that were tried or considered]
Breaking change: [yes/no — if yes, describe what breaks]

Conventional Commits format:
- First line: type(scope): short description (max 72 chars, imperative mood)
  Types: feat, fix, refactor, docs, test, chore, perf, style
- Blank line
- Body: explain the why, not the what (the diff shows what). Wrap at 72 chars.
- Footer (if applicable): BREAKING CHANGE: or Closes #issue-number

Write the complete commit message including body.

What this does: Forces the three elements that make commit messages useful — the why, the effect, and the trade-offs. The Conventional Commits format adds machine-readability for automated changelog generation.

⚡ Pro tip: Add "write the commit message as if the reader has never seen the codebase and has only the commit message and the diff to understand this change." This perspective shift dramatically improves commit message quality — it eliminates the author assumptions that make commit messages opaque to future maintainers.

Breaking Down Each Element

Conventional Commits format — this isn't just style preference. Conventional Commits enables automated semantic versioning (feat → minor bump, fix → patch bump, BREAKING CHANGE → major bump) and automated changelog generation with tools like semantic-release or standard-version. Specifying the format makes your commit history machine-actionable.

Imperative mood — "Add user authentication" not "Added user authentication." This is a Git convention: commit messages describe what the commit does, not what was done. AI frequently uses past tense without this instruction.

The "why" in the body — the most important element. "Fix null pointer in auth middleware" is the what. "The auth middleware was not handling the case where a user account was created via SSO and the local password field was null. Users who authenticated via Google would get a 500 error on any endpoint that checked password history" is the why, and it's infinitely more useful during a 3am incident.

BREAKING CHANGE footer — if you use Conventional Commits tooling, this footer is what triggers a major version bump in semantic versioning. Missing it means a breaking change ships without the version signal that downstream consumers need to prepare.

⚡ Pro tip: For larger changes, ask for a commit message and a PR description: "Write both a git commit message (following Conventional Commits) and a GitHub PR description for this change. The commit message should be concise. The PR description should include: context, what changed, how to test it, and any deployment considerations." The two serve different audiences and different time horizons.

Variations for Different Contexts

For bug fixes with root cause:

Write a Conventional Commits fix message for this bug fix. Include in the body: the symptom users experienced, the root cause (not just the code change), and why this fix resolves it without introducing new issues. Note any edge cases that were considered.

Bug: [describe]
Root cause: [describe]
Fix applied: [describe]

What this does: Bug fix commit messages are the most valuable commit messages in a codebase — they capture the diagnostic reasoning that took hours to arrive at. Preserving it in the commit body means the next person who hits a similar issue has a head start.

For performance improvements:

Write a Conventional Commits perf message for this performance optimization. Include in the body: the baseline metric before the change, the target metric, the actual improvement measured, and the approach taken. Note: if the improvement was measured in a benchmark environment, describe the benchmark setup.

Before: [metric]
After: [metric]
Approach: [describe]

What this does: Performance commit messages without metrics are meaningless. "Improve query performance" could mean 10ms or 10 seconds. Numbers make the message auditable.

For dependency updates:

Write a chore commit message for this dependency update. Include: the package name, old version, new version, why the update was needed (security fix, new feature needed, routine maintenance), and any breaking changes in the updated package that required code changes.

Package: [name]
Old version: [X]
New version: [Y]
Reason: [security/feature/maintenance]

What this does: Dependency updates are the most commonly under-documented commits. A year later, "bump lodash from 4.17.20 to 4.17.21" tells you nothing — but "security fix for CVE-2021-23337 (prototype pollution)" tells you exactly why the update happened.

Save and Reuse This

The improved commit message prompt structure — what changed, why, effect, trade-offs — is the template for every significant commit. The Conventional Commits format and format instructions stay constant; the content varies.

Building your commit message prompts into your workflow (your IDE, your git hooks, or your AI tool) reduces the activation energy for good commit messages. The easier it is to write a good message, the more consistently the team does it.

PromptABCD is useful here — store your team's commit message prompt alongside your code review and documentation prompts. ⚡ Pro tip: For teams using squash-merge strategy (squashing all PR commits into one on merge), ask the AI to generate the squash commit message from the PR description and commit list: 'Generate a single Conventional Commits squash commit message for this pull request. The message should summarize all the changes in the PR, use the correct type based on the overall change (feat if any feature was added, fix if it's a bug fix only), and include a body covering the motivation and the three most significant individual changes.' Squash commits are the permanent history — they deserve as much care as any other commit.

Your ai prompts git commit messages toolkit means good commit hygiene is always one template away, not dependent on whoever happens to remember the format that week.

Commit Message Automation

For teams that want to enforce commit message standards without manual effort, AI can be integrated into the git workflow itself. A hook that improves commit messages automatically:

Write a git commit-msg hook (shell script) that: reads the developer's draft commit message, sends it to an AI API with instructions to improve it following Conventional Commits format while preserving the developer's intent, and replaces the draft with the improved version. The hook should run only if the message is shorter than 50 characters or doesn't start with a Conventional Commits type.

What this does: Automates the formatting and structure while preserving the developer's actual message. A hook that only activates for short/non-conforming messages respects the developer's autonomy when they've already written a good message.

⚡ Pro tip: For teams adopting Conventional Commits for the first time, ask: "Write a git alias that generates a commit message template based on the current staged diff. The template should have placeholders for: type, scope, short description, and body — making it easy to fill in rather than start from scratch." Reducing the blank-page problem for commit messages is often enough to dramatically improve team-wide commit quality.

Learning from Commit Histories

Commit histories are data. A good commit history tells the story of a codebase's evolution. AI can help extract that story:

Analyze this git log and identify: the three most common change patterns in the last 6 months, which files have the most churn (most commits), and any patterns that suggest recurring issues (frequent fixes in the same area). Suggest what this commit history reveals about the codebase's health.

Git log: [paste git log --oneline output for last 6 months]

What this does: Turns a commit history into a codebase health report — identifying hot spots, recurring bug areas, and change frequency patterns that inform where to invest refactoring effort.

Your ai prompts git commit messages library, combined with a commit message hook and a history analysis prompt, creates a complete commit quality system that improves both individual messages and team-wide patterns over time.