
Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
Execute the full TDD-enforced implementation workflow.
analyst agent
quick-flow-solo-dev agent
presentation-master agent
Quad-modal workflow for creating BMAD modules (Brief + Create + Edit + Validate)
Navigate significant changes during sprint execution by analyzing impact, proposing solutions, and routing for implementation
PRD tri-modal workflow - Create, Validate, or Edit comprehensive PRDs
Create comprehensive product briefs through collaborative step-by-step discovery as creative Business Analyst working with the user as peers.
Generate and manage the sprint status tracking file for Phase 4 implementation, extracting all epics and stories from epic files and tracking their status through the development lifecycle
Identify disruption opportunities and architect business model innovation. This workflow guides strategic analysis of markets, competitive dynamics, and business model innovation to uncover sustainable competitive advantages and breakthrough opportunities.
Craft compelling narratives using proven story frameworks and techniques. This workflow guides users through structured narrative development, applying appropriate story frameworks to create emotionally resonant and engaging stories for any purpose.
Get unstuck by showing what workflow steps come next or answering questions about what to do
Splits large markdown documents into smaller, organized files based on level 2 (default) sections
Initialize production-ready test framework architecture (Playwright or Cypress) with fixtures, helpers, and configuration
Generate requirements-to-tests traceability matrix, analyze coverage, and make quality gate decision (PASS/CONCERNS/FAIL/WAIVED)
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
Comprehensive GitHub code review with AI-powered swarm coordination
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.
tea agent
Deep agentic-flow@alpha integration implementing ADR-001. Eliminates 10,000+ duplicate lines by building claude-flow as specialized extension rather than parallel implementation.
MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.
Reload context from a previous session.
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
workflow-builder agent
dev agent
quinn agent
tech-writer agent
ux-designer agent
brainstorming-coach agent
creative-problem-solver agent
innovation-strategist agent
storyteller agent
Tri-modal workflow for creating, editing, and validating BMAD Core compliant agents
Create structured standalone workflows using markdown-based step architecture (tri-modal: create, validate, edit)
Critical validation workflow that assesses PRD, Architecture, and Epics & Stories for completeness and alignment before implementation. Uses adversarial review approach to find gaps and issues.
Collaborative architectural decision facilitation for AI-agent consistency. Replaces template-driven architecture with intelligent, adaptive conversation that produces a decision-focused architecture document optimized for preventing agent conflicts.
Transform PRD requirements and Architecture decisions into comprehensive stories organized by user value. This workflow requires completed PRD + Architecture documents (UX recommended if UI exists) and breaks down requirements into implementation-ready epics and user stories that incorporate all available technical and design context. Creates detailed, actionable stories with complete acceptance criteria for development teams.
Conduct comprehensive research across multiple domains using current web data and verified sources - Market, Technical, Domain and other research types.
Work with a peer UX Design expert to plan your applications UX patterns, look and feel.
Analyzes and documents brownfield projects by scanning codebase, architecture, and patterns to create comprehensive reference documentation for AI-assisted development
Flexible development - execute tech-specs OR direct instructions with optional planning.
Conversational spec engineering - ask questions, investigate code, produce implementation-ready tech-spec.
Summarize sprint-status.yaml, surface risks, and route to the right implementation workflow.
Facilitate interactive brainstorming sessions using diverse creative techniques and ideation methods
Apply systematic problem-solving methodologies to crack complex challenges. This workflow guides through problem diagnosis, root cause analysis, creative solution generation, evaluation, and implementation planning using proven frameworks.
Clinical copy-editor that reviews text for communication issues
Structural editor that proposes cuts, reorganization,
Generates or updates an index.md of all documents in the specified directory
Orchestrates group discussions between all installed BMAD agents, enabling natural multi-agent conversations
Multi-session learning companion that teaches testing progressively through 7 structured sessions with state persistence
Generate failing acceptance tests before implementation using TDD red-green-refactor cycle
Scaffold CI/CD quality pipeline with test execution, burn-in loops, and artifact collection
Assess non-functional requirements (performance, security, reliability, maintainability) before release with evidence-based validation
Review test quality using comprehensive knowledge base and best practices validation
Web browser automation with AI-optimized snapshots for claude-flow agents
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
Land the plane: commit all changes, push, and confirm clean state
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.
CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow automation.
Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).
Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
Complete security architecture overhaul for claude-flow v3. Addresses critical CVEs (CVE-1, CVE-2, CVE-3) and implements secure-by-default patterns. Use for security-first v3 implementation.
15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
module-builder agent
agent-builder agent
Fast-track trivial changes through the implement-close workflow.
Convert BMAD stories to Beads issues with bidirectional tracking.
Load codebase context into the current session.
Run the full local quality gate across all configured tools.
bmad-master agent
architect agent
pm agent
sm agent
design-thinking-coach agent
Perform an ADVERSARIAL Senior Developer code review that finds 3-10 specific problems in every story. Challenges everything: code quality, test coverage, architecture compliance, security, performance. NEVER accepts `looks good` - must find minimum issues and can auto-fix with user approval.
Create data flow diagrams (DFD) in Excalidraw format
Create system architecture diagrams, ERDs, UML diagrams, or general technical diagrams in Excalidraw format
Create website or app wireframes in Excalidraw format
Create a flowchart visualization in Excalidraw format for processes, pipelines, or logic flows
Create the next user story from epics+stories with enhanced context analysis and direct ready-for-dev marking
Execute a story by implementing tasks/subtasks, writing tests, validating, and updating the story file per acceptance criteria
Generate tests quickly for existing features using standard test patterns
Run after epic completion to review overall success, extract lessons learned, and explore if new information emerged that might impact the next epic
Guide human-centered design processes using empathy-driven methodologies. This workflow walks through the design thinking phases - Empathize, Define, Ideate, Prototype, and Test - to create solutions deeply rooted in user needs.
Cynically review content and produce findings
Expand test automation coverage after implementation or analyze existing codebase to generate comprehensive test suite
Dual-mode workflow: (1) System-level testability review in Solutioning phase, or (2) Epic-level test planning in Implementation phase. Auto-detects mode based on project phase.