# Step 1: Context Discovery & Initialization ## MANDATORY EXECUTION RULES (READ FIRST): - 🛑 NEVER generate content without user input - ✅ ALWAYS treat this as collaborative discovery between technical peers - 📋 YOU ARE A FACILITATOR, not a content generator - 💬 FOCUS on discovering existing project context and technology stack - 🎯 IDENTIFY critical implementation rules that AI agents need - ⚠️ ABSOLUTELY NO TIME ESTIMATES - AI development speed has fundamentally changed ## EXECUTION PROTOCOLS: - 🎯 Show your analysis before taking any action - 📖 Read existing project files to understand current context - 💾 Initialize document and update frontmatter - 🚫 FORBIDDEN to load next step until discovery is complete ## CONTEXT BOUNDARIES: - Variables from workflow.md are available in memory - Focus on existing project files and architecture decisions - Look for patterns, conventions, and unique requirements - Prioritize rules that prevent implementation mistakes ## YOUR TASK: Discover the project's technology stack, existing patterns, and critical implementation rules that AI agents must follow when writing code. ## DISCOVERY SEQUENCE: ### 1. Check for Existing Project Context First, check if project context already exists: - Look for file at `{output_folder}/project-context.md` - If exists: Read complete file to understand existing rules - Present to user: "Found existing project context with {number_of_sections} sections. Would you like to update this or create a new one?" ### 2. Discover Project Technology Stack Load and analyze project files to identify technologies: **Architecture Document:** - Look for `{output_folder}/architecture.md` - Extract technology choices with specific versions - Note architectural decisions that affect implementation **Package Files:** - Check for `package.json`, `requirements.txt`, `Cargo.toml`, etc. - Extract exact versions of all dependencies - Note development vs production dependencies **Configuration Files:** - Look for TypeScript config (`tsconfig.json`) - Build tool configs (webpack, vite, next.config.js, etc.) - Linting and formatting configs (.eslintrc, .prettierrc, etc.) - Testing configurations (jest.config.js, vitest.config.ts, etc.) ### 3. Identify Existing Code Patterns Search through existing codebase for patterns: **Naming Conventions:** - File naming patterns (PascalCase, kebab-case, etc.) - Component/function naming conventions - Variable naming patterns - Test file naming patterns **Code Organization:** - How components are structured - Where utilities and helpers are placed - How services are organized - Test organization patterns **Documentation Patterns:** - Comment styles and conventions - Documentation requirements - README and API doc patterns ### 4. Extract Critical Implementation Rules Look for rules that AI agents might miss: **Language-Specific Rules:** - TypeScript strict mode requirements - Import/export conventions - Async/await vs Promise usage patterns - Error handling patterns specific to the language **Framework-Specific Rules:** - React hooks usage patterns - API route conventions - Middleware usage patterns - State management patterns **Testing Rules:** - Test structure requirements - Mock usage conventions - Integration vs unit test boundaries - Coverage requirements **Development Workflow Rules:** - Branch naming conventions - Commit message patterns - PR review requirements - Deployment procedures ### 5. Initialize Project Context Document Based on discovery, create or update the context document: #### A. Fresh Document Setup (if no existing context) Copy template from `{installed_path}/project-context-template.md` to `{output_folder}/project-context.md` Initialize frontmatter with: ```yaml --- project_name: '{{project_name}}' user_name: '{{user_name}}' date: '{{date}}' sections_completed: ['technology_stack'] existing_patterns_found: { { number_of_patterns_discovered } } --- ``` #### B. Existing Document Update Load existing context and prepare for updates Set frontmatter `sections_completed` to track what will be updated ### 6. Present Discovery Summary Report findings to user: "Welcome {{user_name}}! I've analyzed your project for {{project_name}} to discover the context that AI agents need. **Technology Stack Discovered:** {{list_of_technologies_with_versions}} **Existing Patterns Found:** - {{number_of_patterns}} implementation patterns - {{number_of_conventions}} coding conventions - {{number_of_rules}} critical rules **Key Areas for Context Rules:** - {{area_1}} (e.g., TypeScript configuration) - {{area_2}} (e.g., Testing patterns) - {{area_3}} (e.g., Code organization) {if_existing_context} **Existing Context:** Found {{sections}} sections already defined. We can update or add to these. {/if_existing_context} Ready to create/update your project context. This will help AI agents implement code consistently with your project's standards. [C] Continue to context generation" ## SUCCESS METRICS: ✅ Existing project context properly detected and handled ✅ Technology stack accurately identified with versions ✅ Critical implementation patterns discovered ✅ Project context document properly initialized ✅ Discovery findings clearly presented to user ✅ User ready to proceed with context generation ## FAILURE MODES: ❌ Not checking for existing project context before creating new one ❌ Missing critical technology versions or configurations ❌ Overlooking important coding patterns or conventions ❌ Not initializing frontmatter properly ❌ Not presenting clear discovery summary to user ## NEXT STEP: After user selects [C] to continue, load `./step-02-generate.md` to collaboratively generate the specific project context rules. Remember: Do NOT proceed to step-02 until user explicitly selects [C] from the menu and discovery is confirmed!