name: story-implementation version: 1.0.0 description: >- Dual-variant story implementation with comprehensive validation. Simple: UI/content changes with validation (9 steps, 2-3 days) Standard: Feature implementation with comprehensive validation (15 steps, 4-5 days) Includes Task tool execution requirements. author: BMAD Development Team bmad_version: "4.0.0" # Files included in this expansion pack files: workflows: - story-simple.yml - story-implementation.yml tasks: - approve-story-for-development.md - setup-development-environment.md - implement-story-development.md - consolidate-review-feedback.md - implement-consolidated-fixes.md - validate-consolidated-fixes.md - capture-learning-triage.md - party-mode-learning-review.md - commit-and-prepare-pr.md - create-comprehensive-pr.md - update-epic-progress.md - epic-party-mode-retrospective.md checklists: - story-approval-checklist.md - epic-readiness-checklist.md # Dependencies on core BMAD components dependencies: core_agents: - sm - po - infra-devops-platform - dev - architect - qa - ux-expert core_tasks: - create-next-story - execute-checklist - implement-story-development core_checklists: - story-draft-checklist.md - architect-checklist.md - po-master-checklist.md - story-dod-checklist.md core_templates: - story-tmpl.md # No additional data files required from user required_data: [] # No template variables needed - core tasks handle validation # Post-install message post_install_message: | Story Implementation Pack v1.0.0 ready! Phase 1: Story Preparation (Epic → Story Ready for Development) Phase 2: Implementation (Story Development with Validation) Phase 3: Quality Review (Comprehensive Round 1 + Efficient Round 2+) Phase 4: Learning Extraction (Triage + Collaborative Review) Phase 5: Commit and PR Preparation (Context Generation) Phase 6: PR Creation and Epic Progress (Delivery + Tracking) Features: - Epic validation before story creation - Project-agnostic code generation and build tool integration - Round 1: Comprehensive reviews (Architecture, Business, Process, QA, UX) - Feedback consolidation with REQUIRED-FOR-COMPLETION/QUALITY-STANDARD/IMPROVEMENT classification - Round 2+: Efficient architect-only validation with browser MCP testing - Story status tracking throughout workflow (Draft → Approved → In Progress → Verified → Review → Done → Delivered) - Story-based documentation for evidence and tracking - Learning extraction with structured triage system (6 categories) - Party mode collaborative learning review with team consensus - Comprehensive PR creation with business context and learning insights - Epic progress tracking with learning integration - LLM-optimized documentation with token limits and structured brevity Learning Categories: - ARCH_CHANGE: Architecture improvements and technical debt - FUTURE_EPIC: Epic candidates and feature opportunities - URGENT_FIX: Critical issues requiring immediate attention - PROCESS_IMPROVEMENT: Development workflow enhancements - TOOLING: Infrastructure and automation improvements - KNOWLEDGE_GAP: Team training and skill development needs Epic Retrospective Features: - Automatic trigger when epic reaches 100% completion - Multi-agent collaborative analysis (SM, Architect, PO, Dev, UX-Expert) - Party mode consensus building for epic insights - Strategic pattern identification across all epic stories - Action items for next epic with clear ownership - Epic knowledge base creation for future reference - Seamless integration with final story PR Usage: *workflow story-simple epic_number=X story_number=Y # 9 steps, streamlined for simple changes *workflow story-implementation epic_number=X story_number=Y # 15 steps, comprehensive for features Workflow Selection Guide: - story-simple: UI/UX improvements, content updates, simple bug fixes, minor backend changes - story-implementation: New features, business logic, database changes, cross-system integration ⚠️ Both workflows include complexity validation warnings to ensure appropriate selection. All workflow steps require Task tool execution for proper expansion pack compliance. Built on core bmad-method components for maximum reliability. Complete learning extraction and epic progress tracking in both variants.