AI Tools Compared

A good commit message tells your future self (and teammates) why a change was made, not just what changed. AI commit message generators have gotten good enough that the question is no longer “can AI write a useful commit message” but “which tool produces messages that match my team’s conventions without constant editing.”

Tools Compared

What Makes a Good Commit Message

A well-formatted conventional commit:

feat(auth): add OAuth2 PKCE flow for mobile clients

Implements the authorization code flow with PKCE extension to support
native mobile apps that cannot securely store client secrets.

Adds:
- PKCEChallenge generator using SHA-256
- Code verifier storage in encrypted keychain
- Token exchange endpoint that validates code challenge

Fixes #1234

Elements: type prefix (feat/fix/chore/refactor), scope, subject under 72 chars, body explaining why, and issue references. Most developers skip the body because writing it is tedious — this is exactly where AI helps most.

aicommits

aicommits is the most popular standalone CLI tool. It reads your staged diff and calls an LLM to generate a message.

npm install -g aicommits

aicommits config set OPENAI_KEY=sk-...
aicommits config set type=conventional

git add .
aicommits

# Output (for a Python rate limiter implementation):
# feat(ratelimit): add token bucket rate limiter with Redis backend
# Use this commit message? > Yes

Generate multiple variants to pick the best:

aicommits --generate 5

What aicommits does well: Fast, stays out of the way.

Weaknesses: Generated body is often minimal or missing. For a large diff with multiple logical changes, it generates one message for all of them instead of suggesting split commits.

commitizen with AI hooks

Commitizen enforces a structured commit format via interactive prompts. Adding AI to pre-fill the prompts gives you structure + automation.

# .git/hooks/prepare-commit-msg
#!/bin/bash
DIFF=$(git diff --cached)
if [ -z "$DIFF" ]; then
    exit 0
fi

COMMIT_MSG_FILE=$1

GENERATED=$(curl -s https://api.anthropic.com/v1/messages \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d "{
    \"model\": \"claude-haiku-3-5\",
    \"max_tokens\": 256,
    \"messages\": [{
      \"role\": \"user\",
      \"content\": \"Generate a conventional commit message (type(scope): subject) for this diff. Include a 1-2 sentence body explaining why the change was made. Diff:\n\n$DIFF\"
    }]
  }" | python3 -c "import sys,json; print(json.load(sys.stdin)['content'][0]['text'])")

echo "$GENERATED" > "$COMMIT_MSG_FILE"

Make it executable: chmod +x .git/hooks/prepare-commit-msg

Now git commit opens your editor with an AI-generated message pre-filled. The workflow is faster than writing from scratch and more structured than aicommits.

Claude Code

Claude Code generates commit messages as part of its /commit workflow. It reads the full diff, understands multi-file changes, and produces a message with appropriate scope and body.

claude commit

# Claude Code output for a refactor:
# refactor(database): extract connection pool to singleton module
#
# Pool was being re-initialized on every request, causing connection
# exhaustion under concurrent load. Extracted to module-level singleton
# that initializes once on import.
#
# Pool configuration now reads from DATABASE_POOL_SIZE env var (default: 10).

Claude Code understands the context behind the diff — it reads related files to understand what the change actually does. A diff that shows moving code between files gets a “refactor(module): move X to Y” message, not a message describing raw additions and deletions.

Limitation: Requires being in the Claude Code session, which is heavier than a CLI tool for a quick commit.

Cursor IDE Commit

Cursor generates commit messages from the Source Control panel. Click the sparkle icon next to the commit message field.

For a TypeScript refactor that split a large component:

refactor: extract UserProfile subcomponents

Split monolithic UserProfile into UserAvatar, UserBio, and UserStats
components. No functional changes — pure structural refactor to improve
reusability and enable independent testing.

Quality is on par with Claude Code for most cases. The advantage is speed — you’re already in the IDE, no context switch.

GitHub Copilot Commit (VS Code)

GitHub Copilot in VS Code has a sparkle button in the Source Control commit message box:

# Copilot output for the rate limiter implementation:
"Add Redis-backed rate limiter"

# Missing: type prefix, scope, body explaining why Redis vs in-memory

Copilot’s messages are shorter and less structured. Accurate subject lines but rarely include conventional commit formatting or body text.

Quality Comparison

Tested on 20 commits across feature additions, bug fixes, refactors, and dependency updates.

Tool Conventional Format Body Quality Scope Accuracy Speed
Claude Code Excellent Excellent Excellent Slow (full session)
aicommits (GPT-4o) Good Fair Good Fast
Cursor commit Good Good Good Fast
Copilot commit Poor Poor Good Fast
prepare-commit-msg hook (Claude Haiku) Good Good Good Fast

The prepare-commit-msg hook using Claude Haiku is the best balance for most workflows — fast, cheap (fractions of a cent per commit), and works in any Git workflow regardless of IDE.

# Install the hook system-wide
mkdir -p ~/.git-templates/hooks
# [copy the hook script above]
chmod +x ~/.git-templates/hooks/prepare-commit-msg
git config --global init.templateDir ~/.git-templates
# Existing repos: git init (safe to re-run)

For significant commits (releases, major features), use Claude Code’s /commit — the quality is noticeably better when the context is complex.

Advanced Hook: Custom Commit Messages for Different Types

Some teams want different message formats for different change types:

#!/bin/bash
# .git/hooks/prepare-commit-msg (advanced version)

DIFF=$(git diff --cached)
CHANGED_FILES=$(git diff --cached --name-only)

# Determine change type from files
if echo "$CHANGED_FILES" | grep -q "^tests/"; then
    CHANGE_TYPE="test"
elif echo "$CHANGED_FILES" | grep -q "^docs/"; then
    CHANGE_TYPE="docs"
elif echo "$CHANGED_FILES" | grep -q "\.yml\|\.yaml\|docker"; then
    CHANGE_TYPE="chore"
else
    CHANGE_TYPE="auto"  # Let AI decide
fi

PROMPT="Generate a conventional commit message for a \`$CHANGE_TYPE\` change.
Diff:
$DIFF"

GENERATED=$(curl -s https://api.anthropic.com/v1/messages \
  -H "x-api-key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d "{
    \"model\": \"claude-haiku-3-5\",
    \"max_tokens\": 256,
    \"messages\": [{\"role\": \"user\", \"content\": \"$PROMPT\"}]
  }" | jq -r '.content[0].text')

echo "$GENERATED" > "$1"

This hook detects the type of change and tells the AI model “this is a test change” or “this is a docs change,” improving message specificity.

Integrating with Conventional Commits Linting

Most teams enforce conventional commit format via pre-commit hooks:

# .pre-commit-config.yaml
repos:
  - repo: https://github.com/compilerla/conventional-pre-commit
    rev: v2.8.0
    hooks:
      - id: conventional-pre-commit
        stages: [commit-msg]
        args:
          - --force-scope
          - --scope-regex=^\(.*\)$
          - --type-enum=feat,fix,docs,style,refactor,perf,test,chore

When commitizen-cli + AI hook work together:

git add .
git commit  # Opens editor with AI-generated message pre-filled
# If message fails lint checks, you edit it
# Lint passes, commit is created

Commit Messages as Documentation

A well-structured repo can generate a changelog automatically:

# Extract all feat() commits from last month
git log --since="2026-02-21" --until="2026-03-21" \
  --grep="^feat" --pretty=format:"%s %b"

# Output:
# feat(auth): add OAuth2 PKCE flow for mobile clients
# Implements the authorization code flow...
#
# feat(api): add rate limiting to user endpoints
# Limits requests to 1000/min per user for fairness...

Tools like changelog-from-commits parse these automatically. AI-generated messages with body text make this feasible.

Multi-Author Commits

For pair programming or code review sessions:

git commit -m "feat(cache): implement Redis-backed session store

Collaborative implementation with @alice and @bob.
Session TTL is configurable via SESSION_TTL env var (default: 1h).
Includes fallback to in-memory cache if Redis is unavailable.

Co-Authored-By: Alice <alice@example.com>
Co-Authored-By: Bob <bob@example.com>"

AI-generated messages can include the Co-Authored-By trailer automatically if you set it in a config file.

Commit Messages for Semantic Release

If using tools like semantic-release (for automatic versioning):

// .releaserc.json
{
  "plugins": [
    [
      "@semantic-release/commit-analyzer",
      {
        "preset": "conventionalcommits"
      }
    ]
  ]
}

Semantic release parses commit messages:

AI-generated messages that follow the format automatically trigger correct versioning. This is why conventional commit format matters.

Team Commit Message Standards

Build a shared standard for your team:

# Commit Message Standard

## Subject Line (First Line)
- Format: `type(scope): subject`
- Max 72 characters
- Imperative mood ("add", not "added" or "adds")
- Types: feat, fix, refactor, perf, test, docs, chore, ci

## Body (Separate with Blank Line)
- Explain WHAT changed and WHY, not HOW
- Wrap at 100 characters
- Reference issue numbers: "Closes #123"
- If breaking change, include: "BREAKING CHANGE: description"

## Example

feat(auth): add OAuth2 PKCE flow for mobile clients

Implements authorization code flow with PKCE extension to support
native mobile apps that cannot securely store client secrets.

- Adds PKCEChallenge generator using SHA-256
- Stores code verifier in encrypted keychain
- Token exchange endpoint validates code challenge

Closes #456

Share this with your AI tool (as system prompt or in hook comment) so generated messages match your standard.

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