GitHub Actions + Claude Code: I Automated My Entire Dev Workflow

I run Claude Code autonomously in GitHub Actions. Not just for code generation — for the entire boring layer of software development: PR reviews, analyzing test failures, generating changelogs, and converting issue specs to implementation stubs.

Here's the exact setup, including the parts that took trial and error to get right.

Why run Claude in CI instead of locally?

Running Claude locally means I'm in the loop. Every PR I push, I manually ask Claude to review it. That's fine for small teams but it doesn't scale — and it means I'm the bottleneck.

In GitHub Actions, Claude runs automatically on every relevant event. By the time I look at the PR notification, there's already an automated review posted as a comment.

Setup: the Claude Code action

Claude Code has an official GitHub Action. Here's the minimal setup:

# .github/workflows/claude-review.yml
name: Claude PR Review

on:
  pull_request:
    types: [opened, synchronize]

jobs:
  review:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0  # Full history for diff context

      - name: Claude Code Review
        uses: anthropics/claude-code-action@beta
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          github_token: ${{ secrets.GITHUB_TOKEN }}
          direct_prompt: |
            Review this PR and post a comment with:
            1. Summary of what changed
            2. Potential bugs or edge cases
            3. Security concerns if any
            4. Suggestions (max 3, only if significant)
            Be concise. Skip praise. Only flag real issues.

The direct_prompt field is where you define what you want Claude to do. It has access to the full repository and the PR diff.

Pattern 1: Automated test failure analysis

When CI tests fail, the failure output is usually there in the logs but understanding why requires context. Claude is good at this:

# .github/workflows/test-analysis.yml
name: Analyze Test Failures

on:
  workflow_run:
    workflows: ["Tests"]
    types: [completed]

jobs:
  analyze:
    if: ${{ github.event.workflow_run.conclusion == 'failure' }}
    runs-on: ubuntu-latest
    permissions:
      contents: read
      issues: write
      pull-requests: write
    steps:
      - uses: actions/checkout@v4

      - name: Download test artifacts
        uses: actions/download-artifact@v4
        with:
          name: test-results
          run-id: ${{ github.event.workflow_run.id }}
          github-token: ${{ secrets.GITHUB_TOKEN }}

      - name: Analyze with Claude
        uses: anthropics/claude-code-action@beta
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          github_token: ${{ secrets.GITHUB_TOKEN }}
          direct_prompt: |
            Tests failed on the latest push. The test output is in test-results/output.txt.

            Analyze the failures and:
            1. Identify the root cause (not just which test failed)
            2. Point to the specific file and line that likely caused it
            3. Suggest a fix or investigation path

            Post this as a comment on the PR that triggered these tests.

This surfaces the analysis automatically — I see the comment when I get the failure notification.

Pattern 2: Changelog generation

Writing changelogs is exactly the kind of task you shouldn't be doing manually:

# .github/workflows/changelog.yml
name: Generate Changelog

on:
  push:
    tags:
      - 'v*'

jobs:
  changelog:
    runs-on: ubuntu-latest
    permissions:
      contents: write
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0

      - name: Get commits since last tag
        id: commits
        run: |
          PREVIOUS_TAG=$(git describe --tags --abbrev=0 HEAD^ 2>/dev/null || echo "")
          if [ -n "$PREVIOUS_TAG" ]; then
            COMMITS=$(git log ${PREVIOUS_TAG}..HEAD --oneline)
          else
            COMMITS=$(git log --oneline -20)
          fi
          echo "commits<<EOF" >> $GITHUB_OUTPUT
          echo "$COMMITS" >> $GITHUB_OUTPUT
          echo "EOF" >> $GITHUB_OUTPUT

      - name: Generate changelog with Claude
        uses: anthropics/claude-code-action@beta
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          github_token: ${{ secrets.GITHUB_TOKEN }}
          direct_prompt: |
            Generate a changelog for release ${{ github.ref_name }}.

            Commits since last release:
            ${{ steps.commits.outputs.commits }}

            Format:
            ## What's New in ${{ github.ref_name }}

            ### Features
            - ...

            ### Bug Fixes
            - ...

            ### Breaking Changes
            - ... (only if any)

            Write the changelog to CHANGELOG.md (prepend before existing content).
            Then commit and push the updated CHANGELOG.md.

Pattern 3: Spec-to-stub conversion

When I write a GitHub issue describing a feature, Claude can generate the implementation scaffold:

# .github/workflows/spec-to-stub.yml
name: Issue to Code Stub

on:
  issues:
    types: [labeled]

jobs:
  stub:
    if: contains(github.event.label.name, 'ai-scaffold')
    runs-on: ubuntu-latest
    permissions:
      contents: write
      pull-requests: write
    steps:
      - uses: actions/checkout@v4

      - name: Generate stub from issue
        uses: anthropics/claude-code-action@beta
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          github_token: ${{ secrets.GITHUB_TOKEN }}
          direct_prompt: |
            Issue #${{ github.event.issue.number }}: ${{ github.event.issue.title }}

            ${{ github.event.issue.body }}

            Based on this issue and the existing codebase patterns:
            1. Create the necessary files (stub implementations, not complete code)
            2. Add TODOs where the real logic should go
            3. Follow the exact patterns used in similar existing features
            4. Create a draft PR with these stub files

            Target: create a scaffold that a developer can fill in, not a complete implementation.

Label an issue with ai-scaffold and Claude creates a branch with the stub PR. The developer just fills in the logic.

The permissions model

The key permissions for each pattern:

permissions:
  contents: read       # Read repository files
  contents: write      # Write files, create commits
  pull-requests: write # Post PR comments, create PRs
  issues: write        # Post issue comments
  statuses: write      # Update commit status checks

Grant only what you need. PR review only needs contents: read and pull-requests: write.

Cost management

Running Claude on every PR adds up. A few patterns that help:

# Only run on non-draft PRs
on:
  pull_request:
    types: [opened, synchronize, ready_for_review]

jobs:
  review:
    if: github.event.pull_request.draft == false

# Skip for bots and automated commits
jobs:
  review:
    if: |
      github.actor != 'dependabot[bot]' &&
      !startsWith(github.event.head_commit.message, 'chore: bump')

For a team of 3-5 developers doing 10-15 PRs/week, Claude PR review runs about $15-25/month at current Sonnet pricing. That's less than an hour of a developer's time.

What I've actually automated

• PR review — every non-draft PR gets an automated comment within 2 minutes
• Test failure analysis — when CI fails, Claude posts root cause analysis before I see the notification
• Security scan — on main branch merges, Claude scans for credential leaks and obvious vulnerabilities
• Release notes — tags trigger automated CHANGELOG.md updates and draft release creation

The total setup was about 4 hours. The ongoing time savings are easily 3-4 hours per week.

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