Structured Workflow MCP

# Sample Prompts for Structured Workflow MCP Server This directory contains professionally crafted prompt templates for using the Structured Workflow MCP Server effectively. Each template follows 2024 best practices for AI prompt engineering and includes comprehensive examples. ## Available Workflow Templates ### 🔧 [Refactor Workflow](./refactor_workflow_prompt.md) **Use when**: Improving existing code quality, architecture, or maintainability - Template for legacy code modernization - SOLID principles compliance - Performance optimization - Architecture improvements ### ✨ [Feature Development Workflow](./feature_workflow_prompt.md) **Use when**: Building new functionality with integrated testing - New feature implementation - User story development - API endpoint creation - Component development ### 🧪 [Test Workflow](./test_workflow_prompt.md) **Use when**: Improving test coverage for existing code - Unit test development - Integration test suites - Coverage gap analysis - Test strategy implementation ### 🔴🟢🔵 [Test-Driven Development (TDD) Workflow](./tdd_workflow_prompt.md) **Use when**: Building new features using Red-Green-Refactor methodology - Strict TDD implementation - Behavior-driven development - Test-first approach - Quality-focused development ### ⚙️ [Custom Workflow](./custom_workflow_prompt.md) **Use when**: Standard workflows don't fit your specific needs - Legacy system migrations - Compliance projects - Multi-team coordination - Specialized development processes ## How to Use These Templates ### 1. Choose Your Workflow Type Select the template that best matches your current task: - **Existing code needs improvement?** → Refactor Workflow - **Building something new with known requirements?** → Feature Workflow - **Need better test coverage?** → Test Workflow - **Want to practice TDD?** → TDD Workflow - **Have unique requirements?** → Custom Workflow ### 2. Copy and Customize Each template provides: - **Quick Copy-Paste Template**: Minimal version for fast use - **Best Practices Template**: Detailed version with all options - **Complete Example**: Real-world usage demonstration - **Customization Guide**: How to fill in placeholders effectively ### 3. Follow the Structure All templates include these key components: - **Context Setting**: Project background and constraints - **Clear Objectives**: Specific, measurable goals - **Success Criteria**: How you'll know when you're done - **Technical Requirements**: Implementation constraints and preferences ## Template Features ### 📋 Placeholder-Based Design Templates use `[PLACEHOLDER]` format for easy customization: ``` Project: [PROJECT_NAME] Language: [PROGRAMMING_LANGUAGE] Objective: [DETAILED_DESCRIPTION] ``` ### 🎯 Best Practices Integration Based on 2024 AI prompt engineering research: - **Specificity**: Clear, detailed requirements over vague descriptions - **Context**: Comprehensive background information - **Structure**: Organized sections for better AI understanding - **Emotional stimuli**: Phrases that improve AI performance - **Step-by-step guidance**: Systematic approach requests ### 🔧 MCP Server Integration All templates properly integrate with the Structured Workflow MCP Server: - Correct tool names and calling patterns - Platform prefix guidance for compatibility - Output artifact requirements - Phase progression expectations ### 🌐 Platform Compatibility Templates include guidance for different AI platforms: - Tool name prefix variations (`mcp_`, `mcp7_`, etc.) - Discovery tools for checking available commands - Error troubleshooting guidance ## Advanced Usage Tips ### 🎨 Customization Best Practices 1. **Be Specific**: Replace placeholders with precise, detailed information 2. **Provide Context**: Include relevant background about your codebase and constraints 3. **Set Clear Goals**: Define measurable success criteria 4. **Consider Your Team**: Tailor language and complexity to your team's expertise ### 🚀 Performance Optimization - Use emotional context: "This is critical for our Q4 goals" - Request systematic approach: "Take a deep breath and work through this step-by-step" - Specify quality focus: "This needs to be production-ready" - Include constraints upfront: "Cannot modify the database schema" ### 🔍 Troubleshooting If you encounter issues: 1. Check tool name prefixes for your platform 2. Use `mcp__structured-workflow__discover_workflow_tools` to see available commands 3. Verify MCP server is properly connected 4. Review the output artifact requirements ## Contributing These templates are based on: - **Claude Code best practices** from Anthropic engineering team - **2024 prompt engineering research** from academic and industry sources - **Real-world usage patterns** from development teams - **MCP server design principles** and workflow guidance To improve these templates: 1. Test with real projects 2. Note areas where templates could be clearer 3. Identify missing use cases 4. Submit feedback or improvements ## Version Information - **MCP Server Version**: v0.2.3 - **Template Version**: 1.0 - **Last Updated**: 2025-07-03 - **Compatibility**: All MCP-compatible AI platforms --- **Note**: These templates are designed to work with any AI assistant that supports the Model Context Protocol (MCP), including Claude Code, and other compatible systems.