laurigates/workflow-dev

/workflow:dev

Automated development loop with issue creation, TDD, and CI monitoring.

When to Use This Skill

| Use this skill when... | Use X instead when... | |------------------------|----------------------| | Running a continuous loop that turns test failures into issues, then resolves them | Inspecting an existing workflow run or debugging CI failures (/workflow:github-actions-inspection) | | Automating the full issue → branch → PR → green-CI cycle through the backlog | Generating a reusable auto-fix workflow file for multiple repos (/workflow:github-workflow-auto-fix --reusable) | | Wanting Claude to pick the next issue and drive it through TDD without user input | Searching upstream OSS issues for known errors or workarounds (/workflow:github-issue-search) |

Context

• Current branch: !git branch --show-current
• Working tree: !git status --porcelain
• Project type: !find . -maxdepth 1 \( -name "package.json" -o -name "Cargo.toml" -o -name "pyproject.toml" -o -name "go.mod" -o -name "manage.py" \) -type f

Open issues are fetched during execution (requires a configured git remote).

Parameters

Parse from $ARGUMENTS:

• --max-cycles <n>: Limit to N issue resolution cycles (default: unlimited)
• --focus <bug|feature|test>: Only work on issues with matching label
• --quick-wins: Only pick issues estimated < 30 minutes
• --test-only: Only create issues for test failures; skip implementation
• --dry-run: Explain what would be done without making changes

Execution

Execute this automated development loop:

Step 1: Set up environment and assess state

1. Ensure on main branch and sync

git switch main
git pull

2. Run the project's test suite

• Detect project type (check for manage.py, package.json, Cargo.toml, etc.)
• Run appropriate test command:
  • Django: python manage.py test
  • Node.js: npm test
  • Rust: cargo test
  • Python: pytest or python -m pytest
  • Go: go test ./...

3. Create GitHub issues for any test failures

• For each failing test, use github:create_issue with:
  • Title: "Test failure: {test_name}"
  • Body: Include error output, stack trace, and failure context
  • Labels: ["bug", "test-failure"]

4. List current repository issues

• Use github:list_issues with state=open
• Filter out issues that are blocked or need external input

Step 2: Select issue to work on

Select issues using this priority order:

1. Critical bugs: Issues labeled priority: critical or bug + high priority
2. Test failures: Issues just created from failing tests (highest priority)
3. Quick wins: Issues labeled good first issue or estimated < 1 hour
4. High-impact features: Issues with most reactions/comments
5. Technical debt: Oldest issues labeled technical-debt or refactor

Selection criteria (must meet ALL):

• Has clear acceptance criteria in description
• Not labeled blocked or waiting-for-input
• Not already assigned to someone else
• Can reasonably be completed in a single PR

If no suitable issues found:

• Run dependency audit (npm audit, pip-audit, cargo audit)
• Create issues for security vulnerabilities
• Run linting tools and create issues for violations

Step 3: Implement solution

For the selected issue, repeat until CI passes:

5. Create feature branch

git switch -c fix/issue-{number}-{brief-description}

6. Gather implementation context

• ALWAYS use Context7 MCP to fetch current documentation for relevant libraries/frameworks before implementation
• Use context7:resolve-library-id followed by context7:get-library-docs for any tools mentioned
• Read issue description and any linked documentation
• Review related issues and PRs for context
• For package managers (uv, npm, bun, etc.): Always fetch current best practices via Context7 before suggesting commands

7. Implement solution using TDD

• RED: Write a failing test (if test doesn't already exist)
• GREEN: Write minimal code to make the test pass
• REFACTOR: Improve code quality while keeping tests green
• Follow language-specific best practices from Claude Code Guidelines

8. Commit changes

git add <files>
git commit -m "fix: resolve issue #{number} - {brief description}"

• Use conventional commit format
• Reference issue number in commit message

9. Push branch

git push origin fix/issue-{number}-{brief-description}

10. Create pull request

• Use github:create_pull_request with:
  • Title: "fix: resolve issue #{number} - {brief description}"
  • Body: "Fixes #{number}" plus description of changes
  • Include testing notes and any breaking changes

11. Monitor CI status

• Use GitHub MCP to check workflow status
• Wait for all checks to start and complete

12. Fix CI failures (if any)

• Use github:get_pull_request_status to check specific failures
• Analyze workflow logs to understand failures
• Implement fixes and push additional commits
• Repeat until all checks pass

Step 4: Complete and loop

13. Verify CI success

• Confirm all required checks are green
• Ensure no failing workflows remain

14. Close the issue

• Use github:update_issue to close with state closed
• Add comment referencing the closing PR

15. Return to Step 1

• Go back to environment setup
• Continue the loop for the next issue

Configuration Options

Handle these command variations:

• /workflow:dev - Run continuous loop until stopped
• /workflow:dev --max-cycles 3 - Limit to 3 issue resolution cycles
• /workflow:dev --focus bug - Only work on issues labeled "bug"
• /workflow:dev --quick-wins - Only pick issues estimated < 30 minutes
• /workflow:dev --test-only - Only create issues for test failures; implementation handled separately
• /workflow:dev --dry-run - Explain what would be done without making changes

Error Handling

Issue too complex to complete:

• Add comment: "This issue requires more detailed analysis - skipping for now"
• Add label needs-investigation
• Skip to next issue in priority order

Persistent CI failures (3+ attempts):

• Create new issue titled "CI Pipeline Issue: {workflow_name} failing"
• Include workflow logs and error details
• Label as ci-infrastructure
• Skip current issue and continue with next

No issues available:

• Run automated maintenance tasks:
  • Dependency updates (npm update, pip install --upgrade, etc.)
  • Security audits and create issues for vulnerabilities
  • Code quality scans (linting) and create issues for violations
• If still no work, report completion and wait for new issues

Git/GitHub API errors:

• Retry operations up to 3 times
• If persistent, report error and pause loop
• Suggest manual intervention steps

Success Reporting

After each completed issue, report:

✅ Issue #{number} resolved successfully!

Branch: fix/issue-{number}-{description}
PR: #{pr_number} - {pr_title}
CI Status: ✅ All checks passing
Time: {duration}

Continuing to next issue...

Loop Termination

Stop the loop when:

• User interrupts the process
• --max-cycles limit reached
• No suitable issues remain after thorough search
• Critical error requires manual intervention

Provide final summary:

🏁 DevLoop completed!

📊 Summary:
- Issues resolved: {count}
- PRs created: {count}
- Tests added/fixed: {count}
- Total time: {duration}

📋 Recommendations:
- Review open PRs for merge
- Consider upgrading dependencies
- Add more test coverage for uncovered code

Integration Notes

Required tools:

• GitHub MCP for all GitHub operations
• Context7 MCP for documentation lookup (REQUIRED before any tool usage)
• Git command line access
• Project-specific testing tools
• Modern package managers: uv (Python), npm/bun (JavaScript), cargo (Rust)

Repository requirements:

• Clean git working directory (or only intended changes)
• GitHub Actions or other CI configured
• Issue templates and labels configured
• Branch protection requiring PR reviews

Best practices:

• Always use GitHub MCP's context toolset for repository awareness
• Follow TDD principles strictly - no production code without tests
• Keep commits small and focused
• Use conventional commit messages
• Reference issues in all commits and PRs