ABSOLUTE RULES:
- ALL operations MUST be concurrent/parallel in a single message
- NEVER save working files, text/mds and tests to the root folder
- ALWAYS organize files in appropriate subdirectories
- USE CLAUDE CODE'S TASK TOOL for spawning agents concurrently, not just MCP
MANDATORY PATTERNS:
- TodoWrite: ALWAYS batch ALL todos in ONE call (5-10+ todos minimum)
- Task tool (Claude Code): ALWAYS spawn ALL agents in ONE message with full instructions
- File operations: ALWAYS batch ALL reads/writes/edits in ONE message
- Bash commands: ALWAYS batch ALL terminal operations in ONE message
- Memory operations: ALWAYS batch ALL memory store/retrieve in ONE message
Claude Code's Task tool is the PRIMARY way to spawn agents:
// ✅ CORRECT: Use Claude Code's Task tool for parallel agent execution
[Single Message]:
Task("Research agent", "Analyze requirements and patterns...", "researcher")
Task("Coder agent", "Implement core features...", "coder")
Task("Tester agent", "Create comprehensive tests...", "tester")
Task("Reviewer agent", "Review code quality...", "reviewer")
Task("Architect agent", "Design system architecture...", "system-architect")MCP tools are ONLY for coordination setup:
mcp__claude-flow__swarm_init- Initialize coordination topologymcp__claude-flow__agent_spawn- Define agent types for coordinationmcp__claude-flow__task_orchestrate- Orchestrate high-level workflows
NEVER save to root folder. Use these directories:
/src- Source code files/tests- Test files/docs- Documentation and markdown files/config- Configuration files/scripts- Utility scripts/examples- Example code
This project uses SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) methodology with Claude-Flow orchestration for systematic Test-Driven Development.
npx claude-flow sparc modes- List available modesnpx claude-flow sparc run <mode> "<task>"- Execute specific modenpx claude-flow sparc tdd "<feature>"- Run complete TDD workflownpx claude-flow sparc info <mode>- Get mode details
npx claude-flow sparc batch <modes> "<task>"- Parallel executionnpx claude-flow sparc pipeline "<task>"- Full pipeline processingnpx claude-flow sparc concurrent <mode> "<tasks-file>"- Multi-task processing
npm run build- Build projectnpm run test- Run testsnpm run lint- Lintingnpm run typecheck- Type checking
- Specification - Requirements analysis (
sparc run spec-pseudocode) - Pseudocode - Algorithm design (
sparc run spec-pseudocode) - Architecture - System design (
sparc run architect) - Refinement - TDD implementation (
sparc tdd) - Completion - Integration (
sparc run integration)
- Modular Design: Files under 500 lines
- Environment Safety: Never hardcode secrets
- Test-First: Write tests before implementation
- Clean Architecture: Separate concerns
- Documentation: Keep updated
coder, reviewer, tester, planner, researcher
hierarchical-coordinator, mesh-coordinator, adaptive-coordinator, collective-intelligence-coordinator, swarm-memory-manager
byzantine-coordinator, raft-manager, gossip-coordinator, consensus-builder, crdt-synchronizer, quorum-manager, security-manager
perf-analyzer, performance-benchmarker, task-orchestrator, memory-coordinator, smart-agent
github-modes, pr-manager, code-review-swarm, issue-tracker, release-manager, workflow-automation, project-board-sync, repo-architect, multi-repo-swarm
sparc-coord, sparc-coder, specification, pseudocode, architecture, refinement
backend-dev, mobile-dev, ml-developer, cicd-engineer, api-docs, system-architect, code-analyzer, base-template-generator
tdd-london-swarm, production-validator
migration-planner, swarm-init
- Task tool: Spawn and run agents concurrently for actual work
- File operations (Read, Write, Edit, MultiEdit, Glob, Grep)
- Code generation and programming
- Bash commands and system operations
- Implementation work
- Project navigation and analysis
- TodoWrite and task management
- Git operations
- Package management
- Testing and debugging
- Swarm initialization (topology setup)
- Agent type definitions (coordination patterns)
- Task orchestration (high-level planning)
- Memory management
- Neural features
- Performance tracking
- GitHub integration
KEY: MCP coordinates the strategy, Claude Code's Task tool executes with real agents.
# Add MCP servers (Claude Flow required, others optional)
claude mcp add claude-flow npx claude-flow@alpha mcp start
claude mcp add ruv-swarm npx ruv-swarm mcp start # Optional: Enhanced coordination
claude mcp add flow-nexus npx flow-nexus@latest mcp start # Optional: Cloud featuresswarm_init, agent_spawn, task_orchestrate
swarm_status, agent_list, agent_metrics, task_status, task_results
memory_usage, neural_status, neural_train, neural_patterns
github_swarm, repo_analyze, pr_enhance, issue_triage, code_review
benchmark_run, features_detect, swarm_monitor
Flow-Nexus extends MCP capabilities with 70+ cloud-based orchestration tools:
Key MCP Tool Categories:
- Swarm & Agents:
swarm_init,swarm_scale,agent_spawn,task_orchestrate - Sandboxes:
sandbox_create,sandbox_execute,sandbox_upload(cloud execution) - Templates:
template_list,template_deploy(pre-built project templates) - Neural AI:
neural_train,neural_patterns,seraphina_chat(AI assistant) - GitHub:
github_repo_analyze,github_pr_manage(repository management) - Real-time:
execution_stream_subscribe,realtime_subscribe(live monitoring) - Storage:
storage_upload,storage_list(cloud file management)
Authentication Required:
- Register:
mcp__flow-nexus__user_registerornpx flow-nexus@latest register - Login:
mcp__flow-nexus__user_loginornpx flow-nexus@latest login - Access 70+ specialized MCP tools for advanced orchestration
- Optional: Use MCP tools to set up coordination topology
- REQUIRED: Use Claude Code's Task tool to spawn agents that do actual work
- REQUIRED: Each agent runs hooks for coordination
- REQUIRED: Batch all operations in single messages
// Single message with all agent spawning via Claude Code's Task tool
[Parallel Agent Execution]:
Task("Backend Developer", "Build REST API with Express. Use hooks for coordination.", "backend-dev")
Task("Frontend Developer", "Create React UI. Coordinate with backend via memory.", "coder")
Task("Database Architect", "Design PostgreSQL schema. Store schema in memory.", "code-analyzer")
Task("Test Engineer", "Write Jest tests. Check memory for API contracts.", "tester")
Task("DevOps Engineer", "Setup Docker and CI/CD. Document in memory.", "cicd-engineer")
Task("Security Auditor", "Review authentication. Report findings via hooks.", "reviewer")
// All todos batched together
TodoWrite { todos: [...8-10 todos...] }
// All file operations together
Write "backend/server.js"
Write "frontend/App.jsx"
Write "database/schema.sql"1️⃣ BEFORE Work:
npx claude-flow@alpha hooks pre-task --description "[task]"
npx claude-flow@alpha hooks session-restore --session-id "swarm-[id]"2️⃣ DURING Work:
npx claude-flow@alpha hooks post-edit --file "[file]" --memory-key "swarm/[agent]/[step]"
npx claude-flow@alpha hooks notify --message "[what was done]"3️⃣ AFTER Work:
npx claude-flow@alpha hooks post-task --task-id "[task]"
npx claude-flow@alpha hooks session-end --export-metrics true// Step 1: MCP tools set up coordination (optional, for complex tasks)
[Single Message - Coordination Setup]:
mcp__claude-flow__swarm_init { topology: "mesh", maxAgents: 6 }
mcp__claude-flow__agent_spawn { type: "researcher" }
mcp__claude-flow__agent_spawn { type: "coder" }
mcp__claude-flow__agent_spawn { type: "tester" }
// Step 2: Claude Code Task tool spawns ACTUAL agents that do the work
[Single Message - Parallel Agent Execution]:
// Claude Code's Task tool spawns real agents concurrently
Task("Research agent", "Analyze API requirements and best practices. Check memory for prior decisions.", "researcher")
Task("Coder agent", "Implement REST endpoints with authentication. Coordinate via hooks.", "coder")
Task("Database agent", "Design and implement database schema. Store decisions in memory.", "code-analyzer")
Task("Tester agent", "Create comprehensive test suite with 90% coverage.", "tester")
Task("Reviewer agent", "Review code quality and security. Document findings.", "reviewer")
// Batch ALL todos in ONE call
TodoWrite { todos: [
{id: "1", content: "Research API patterns", status: "in_progress", priority: "high"},
{id: "2", content: "Design database schema", status: "in_progress", priority: "high"},
{id: "3", content: "Implement authentication", status: "pending", priority: "high"},
{id: "4", content: "Build REST endpoints", status: "pending", priority: "high"},
{id: "5", content: "Write unit tests", status: "pending", priority: "medium"},
{id: "6", content: "Integration tests", status: "pending", priority: "medium"},
{id: "7", content: "API documentation", status: "pending", priority: "low"},
{id: "8", content: "Performance optimization", status: "pending", priority: "low"}
]}
// Parallel file operations
Bash "mkdir -p app/{src,tests,docs,config}"
Write "app/package.json"
Write "app/src/server.js"
Write "app/tests/server.test.js"
Write "app/docs/API.md"Message 1: mcp__claude-flow__swarm_init
Message 2: Task("agent 1")
Message 3: TodoWrite { todos: [single todo] }
Message 4: Write "file.js"
// This breaks parallel coordination!- 84.8% SWE-Bench solve rate
- 32.3% token reduction
- 2.8-4.4x speed improvement
- 27+ neural models
- Auto-assign agents by file type
- Validate commands for safety
- Prepare resources automatically
- Optimize topology by complexity
- Cache searches
- Auto-format code
- Train neural patterns
- Update memory
- Analyze performance
- Track token usage
- Generate summaries
- Persist state
- Track metrics
- Restore context
- Export workflows
- 🚀 Automatic Topology Selection
- ⚡ Parallel Execution (2.8-4.4x speed)
- 🧠 Neural Training
- 📊 Bottleneck Analysis
- 🤖 Smart Auto-Spawning
- 🛡️ Self-Healing Workflows
- 💾 Cross-Session Memory
- 🔗 GitHub Integration
- Start with basic swarm init
- Scale agents gradually
- Use memory for context
- Monitor progress regularly
- Train patterns from success
- Enable hooks automation
- Use GitHub tools first
- Documentation: https://github.com/ruvnet/claude-flow
- Issues: https://github.com/ruvnet/claude-flow/issues
- Flow-Nexus Platform: https://flow-nexus.ruv.io (registration required for cloud features)
Remember: Claude Flow coordinates, Claude Code creates!
Do what has been asked; nothing more, nothing less. NEVER create files unless they're absolutely necessary for achieving your goal. ALWAYS prefer editing an existing file to creating a new one. NEVER proactively create documentation files (*.md) or README files. Only create documentation files if explicitly requested by the User. Never save working files, text/mds and tests to the root folder.
CRITICAL RULE: Always build to spec. No implementation changes unless outlined in specification documents.
These principles are NON-NEGOTIABLE and apply to ALL work:
-
SPEC-FIRST DEVELOPMENT
- Update or create specs FIRST in
docs/specs/before ANY implementation - Specs are the single source of truth
- Never implement unspecified behavior
- Update or create specs FIRST in
-
ADR FOR ARCHITECTURE
- Create/modify ADRs for architecturally significant changes
- ALWAYS follow ADR Implementation Spec
- Save ADRs to
docs/adr/ - Reference ADR template:
docs/adr/000-adr-template.md
-
DRY (Don't Repeat Yourself)
- Identify reusable patterns and abstractions
- Extract common logic into shared utilities
- If you write it twice, refactor it once
-
NO MOCKS - PRODUCTION READY CODE ONLY
- Write real, production-ready implementations
- No mock objects, fake data, or stub implementations
- If external dependencies are needed, use proper integration patterns
-
TDD (Test-Driven Development)
- Write tests FIRST, then implement
- Tests define the expected behavior
- All code must have corresponding tests
-
DOCUMENTATION UPDATES
- Review and update ALL relevant docs with every change:
README.md- User guide (
docs/user-guide.md) - CLI spec (
docs/specs/09-cli-interface-spec.md) - Any affected specification documents
- Review and update ALL relevant docs with every change:
MANDATORY: When any task requires planning (new features, refactors, multi-file changes, architectural decisions), you MUST use /plan mode. Do not skip planning and jump straight to implementation.
-
Before implementing ANY feature:
- Check if feature is defined in
/docs/specs/ - If NOT defined → Create/update the spec first, then implement
- If defined → Implement exactly as specified
- Check if feature is defined in
-
Specification Documents (in order of dependency):
Spec Document Purpose 01 Puzzle Engine Sudoku generation, validation, rules 02 Memory System AgentDB integration & persistence 03 GRASP Loop Generate, Review, Absorb, Synthesize, Persist 04 Attention Mechanism Focus and priority system 05 Dreaming Pipeline 5-phase consolidation 06 Benchmarking Framework Performance testing 07 Integration Orchestration System orchestration 08 AgentDB Integration Native AgentDB features 09 CLI Interface Command-line interface 10 Terminal UI Interactive TUI with Ink 11 LLM Integration AI model Sudoku player 12 Puzzle Generation Seeded random puzzles 13 Profile Management AI model connection profiles 14 Console Menu TUI console & help system 15 Batch Testing A/B testing & iterative learning scripts 16 AISP Mode AI Sudoku Protocol validation 17 ADR Implementation Architecture Decision Records 18 Algorithm Versioning Versioned algorithm system 19 Failure Learning Learning from failures -
When specs conflict with implementation ideas:
- Specs are authoritative
- Propose spec updates if needed
- Never implement unspecified behavior
-
Verification Checklist (before any PR):
- All new types defined in specs
- All event types registered in Spec 07
- All CLI commands match Spec 09
- All TUI screens match Spec 10
- Tests verify spec compliance
- ADR created for architectural changes (per Spec 17)
- Documentation updated (README, user guide, CLI spec)
- No mock implementations - production code only
- Consistency: All components follow the same contracts
- Traceability: Every feature maps to a specification
- Reviewability: Changes are validated against specs
- Maintainability: Specs serve as living documentation
- Quality: TDD + no mocks = production-ready from day one