Skill: tc1993/auto-dev-pipeline (version 1.0.0)

--- name: auto-dev-pipeline description: Complete automated development pipeline for one-person companies. Use when a user provides a simple app idea and wants a fully automated development process from requirements to tested code. This skill coordinates prd-skill, dev-skill, and qa-skill to create a seamless PRD → Development → Testing workflow without manual intervention. --- # Auto Dev Pipeline - One-Person Company Development Automation ## Overview The Auto Dev Pipeline is a complete automated development system that transforms natural language app ideas into fully tested iOS applications. It orchestrates three specialized skills to create a seamless, hands-off development process: 1. **PRD Generation** (`prd-skill`): Requirements → Structured PRD 2. **Development** (`dev-skill`): PRD → SwiftUI iOS Code 3. **Quality Assurance** (`qa-skill`): Code → Test Cases & Validation ## Pipeline Architecture ### 1. Trigger Mechanism The pipeline is triggered by natural language app ideas: - "做一个待办事项App" - "开发一个健身追踪应用" - "创建一个社交网络应用" ### 2. Automated Coordination The pipeline uses OpenClaw's session management to automatically: 1. Spawn `prd-skill` sub-agent with user requirements 2. Monitor PRD completion and trigger `dev-skill` 3. Monitor code generation and trigger `qa-skill` 4. Collect final outputs and provide summary ### 3. Data Flow ``` User Input → prd-skill → PRD Document → dev-skill → SwiftUI Project → qa-skill → Test Suite ``` ## Complete Workflow ### Phase 1: Requirements Analysis (prd-skill) **Input:** Natural language app description **Process:** 1. Parse and analyze requirements 2. Generate structured PRD with: - Product overview and target audience - Functional requirements with priorities - User flows and screen specifications - Technical requirements and constraints 3. Save PRD to `output/prd/[timestamp]-[app-name].md` **Auto-Trigger:** Upon PRD completion, spawn `dev-skill` with PRD as input ### Phase 2: Development Implementation (dev-skill) **Input:** PRD document from Phase 1 **Process:** 1. Analyze PRD for technical requirements 2. Generate complete SwiftUI project with: - MVVM architecture - Data models and services - UI components and navigation - Business logic implementation 3. Create Xcode project in `output/dev/[app-name]/` **Auto-Trigger:** Upon code generation, spawn `qa-skill` with project as input ### Phase 3: Quality Assurance (qa-skill) **Input:** SwiftUI project from Phase 2 **Process:** 1. Analyze code structure and requirements 2. Generate comprehensive test suite: - Unit tests for business logic - UI tests for user flows - Integration tests for data flow 3. Create test documentation and quality report 4. Save to `output/qa/[app-name]-tests/` **Completion:** Pipeline ends with final summary and deliverables ## Session Management ### Sub-Agent Spawning ```python # Example coordination logic def trigger_pipeline(user_requirements): # Step 1: Spawn PRD skill prd_session = sessions_spawn( task=f"Generate PRD for: {user_requirements}", runtime="subagent", agentId="prd-skill" ) # Step 2: Monitor and trigger dev skill wait_for_completion(prd_session) prd_output = read_prd_output() dev_session = sessions_spawn( task=f"Develop iOS app from PRD: {prd_output}", runtime="subagent", agentId="dev-skill" ) # Step 3: Monitor and trigger QA skill wait_for_completion(dev_session) code_output = read_code_output() qa_session = sessions_spawn( task=f"Generate tests for: {code_output}", runtime="subagent", agentId="qa-skill" ) # Step 4: Collect results wait_for_completion(qa_session) return compile_final_report() ``` ### Error Handling - **PRD Generation Failures**: Retry with clarified requirements - **Code Generation Errors**: Fallback to simpler implementation - **Test Generation Issues**: Provide manual test guidelines - **Session Timeouts**: Resume from last successful checkpoint ## Output Structure ``` output/ ├── prd/ │ ├── 20240319-1430-todo-app.md │ └── 20240319-1500-fitness-tracker.md ├── dev/ │ ├── TodoApp/ │ │ ├── TodoApp.xcodeproj │ │ ├── Sources/ │ │ └── README.md │ └── FitnessTracker/ │ ├── FitnessTracker.xcodeproj │ ├── Sources/ │ └── README.md └── qa/ ├── TodoApp-tests/ │ ├── UnitTests/ │ ├── UITests/ │ └── TestReport.md └── FitnessTracker-tests/ ├── UnitTests/ ├── UITests/ └── TestReport.md ``` ## Example: Complete Pipeline Execution ### User Input "做一个待办事项App，支持分类、提醒和分享功能" ### Pipeline Execution 1. **Phase 1 (PRD)**: 2 minutes - Output: `output/prd/20240319-1430-todo-app.md` - Contains: 5 sections, 15 features, technical specs 2. **Phase 2 (Development)**: 5 minutes - Output: `output/dev/TodoApp/` (Xcode project) - Contains: 12 Swift files, Core Data model, UI components 3. **Phase 3 (QA)**: 3 minutes - Output: `output/qa/TodoApp-tests/` (Test suite) - Contains: 28 test cases, test plan, quality report ### Final Delivery - **Total Time**: 10 minutes - **Code Coverage**: 85% - **Features Implemented**: 12/15 (P0+P1) - **Test Cases**: 28 automated tests - **Ready for**: Xcode build and deployment ## Configuration Options ### Model Selection ```yaml pipeline: prd_model: "deepseekchat" # For requirements analysis dev_model: "deepseekchat" # For code generation qa_model: "deepseekchat" # For test generation ``` ### Output Customization ```yaml output: directory: "./auto-dev-output" keep_intermediate: true generate_readme: true include_build_instructions: true ``` ### Quality Settings ```yaml quality: min_code_coverage: 70 require_ui_tests: true accessibility_check: true performance_benchmarks: true ``` ## Best Practices ### For Users 1. **Be Specific**: Provide clear app descriptions 2. **Set Expectations**: Understand MVP vs full feature set 3. **Review Outputs**: Check PRD before development starts 4. **Provide Feedback**: Help improve pipeline accuracy ### For Pipeline Maintenance 1. **Monitor Performance**: Track execution times and success rates 2. **Update Skills**: Keep prd/dev/qa skills current with best practices 3. **Collect Metrics**: Measure code quality and user satisfaction 4. **Iterate Improvements**: Continuously enhance automation logic ## Troubleshooting ### Common Issues 1. **Vague Requirements**: Pipeline asks for clarification 2. **Complex Features**: May require manual intervention 3. **Technical Constraints**: iOS limitations are documented 4. **Timeouts**: Pipeline resumes from last checkpoint ### Resolution Steps 1. Check session logs for error details 2. Review intermediate outputs 3. Adjust requirements and retry 4. Contact pipeline maintainer for complex issues ## Future Enhancements ### Planned Features 1. **Deployment Automation**: App Store Connect integration 2. **CI/CD Pipeline**: GitHub Actions automation 3. **Design Generation**: Figma mockup creation 4. **Documentation**: User manuals and API docs 5. **Monitoring**: App analytics and crash reporting ### Integration Opportunities 1. **App Store**: Automated submission and review 2. **Backend Services**: Firebase/CloudKit integration 3. **Analytics**: Mixpanel/Amplitude setup 4. **Marketing**: App store optimization tools


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)