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Claude Code Configuration - SPARC Development Environment

🚨 CRITICAL: Concurrent Execution Rules

ABSOLUTE RULE: ALL operations MUST be concurrent/parallel in ONE message:

🔴 Mandatory Patterns:

  • TodoWrite: ALWAYS batch ALL todos in ONE call (5-10+ minimum)
  • Task tool: ALWAYS spawn ALL agents in ONE message
  • File operations: ALWAYS batch ALL reads/writes/edits
  • Bash commands: ALWAYS batch ALL terminal operations
  • Memory operations: ALWAYS batch ALL store/retrieve

⚡ Golden Rule: "1 MESSAGE = ALL RELATED OPERATIONS"

✅ CORRECT: Everything in ONE message

[Single Message]:
  - TodoWrite { todos: [10+ todos] }
  - Task("Agent 1"), Task("Agent 2"), Task("Agent 3")
  - Read("file1.js"), Read("file2.js")
  - Write("output1.js"), Write("output2.js")
  - Bash("npm install"), Bash("npm test")

❌ WRONG: Multiple messages (6x slower!)

🎯 Claude Code vs MCP Tools

Claude Code Handles ALL:

  • File operations (Read/Write/Edit/Glob/Grep)
  • Code generation & programming
  • Bash commands & system operations
  • TodoWrite & task management
  • Git operations & package management
  • Testing, debugging & implementation

MCP Tools ONLY:

  • Coordination & planning
  • Memory management
  • Performance tracking
  • Swarm orchestration
  • GitHub integration

Key: MCP coordinates, Claude Code executes!

📦 SPARC Commands

Core:

  • npx claude-flow sparc modes - List modes
  • npx claude-flow sparc run <mode> "<task>" - Execute mode
  • npx claude-flow sparc tdd "<feature>" - TDD workflow
  • npx claude-flow sparc batch <modes> "<task>" - Parallel modes
  • npx claude-flow sparc pipeline "<task>" - Full pipeline

Build:

  • npm run build/test/lint/typecheck

🤖 Agent Reference (54 Total)

Core Development

Agent Purpose
coder Implementation
reviewer Code quality
tester Test creation
planner Strategic planning
researcher Information gathering

Swarm Coordination

Agent Purpose
hierarchical-coordinator Queen-led
mesh-coordinator Peer-to-peer
adaptive-coordinator Dynamic topology
collective-intelligence-coordinator Hive-mind
swarm-memory-manager Distributed memory

Specialized

Agent Purpose
backend-dev API development
mobile-dev React Native
ml-developer Machine learning
system-architect High-level design
sparc-coder TDD implementation
production-validator Real validation

GitHub Integration

Agent Purpose
github-modes Comprehensive integration
pr-manager Pull requests
code-review-swarm Multi-agent review
issue-tracker Issue management
release-manager Release coordination

Performance & Consensus

Agent Purpose
perf-analyzer Bottleneck identification
performance-benchmarker Performance testing
byzantine-coordinator Fault tolerance
raft-manager Leader election
consensus-builder Decision-making

🚀 Swarm Patterns

Full-Stack Swarm (8 agents)

Task("Architecture", "...", "system-architect")
Task("Backend", "...", "backend-dev")
Task("Frontend", "...", "mobile-dev")
Task("Database", "...", "coder")
Task("API Docs", "...", "api-docs")
Task("CI/CD", "...", "cicd-engineer")
Task("Testing", "...", "performance-benchmarker")
Task("Validation", "...", "production-validator")

Agent Count Rules

  1. CLI Args First: npx claude-flow@alpha --agents 5
  2. Auto-Decide: Simple (3-4), Medium (5-7), Complex (8-12)

📋 Agent Coordination Protocol

Every Agent MUST:

1️⃣ START:

npx claude-flow@alpha hooks pre-task --description "[task]"
npx claude-flow@alpha hooks session-restore --session-id "swarm-[id]"

2️⃣ DURING (After EVERY step):

npx claude-flow@alpha hooks post-edit --file "[file]" --memory-key "swarm/[agent]/[step]"
npx claude-flow@alpha hooks notify --message "[decision]"

3️⃣ END:

npx claude-flow@alpha hooks post-task --task-id "[task]" --analyze-performance true
npx claude-flow@alpha hooks session-end --export-metrics true

🛠️ MCP Setup

# Add MCP server
claude mcp add claude-flow npx claude-flow@alpha mcp start

Key MCP Tools:

  • mcp__claude-flow__swarm_init - Setup topology
  • mcp__claude-flow__agent_spawn - Create agents
  • mcp__claude-flow__task_orchestrate - Coordinate tasks
  • mcp__claude-flow__memory_usage - Persistent memory
  • mcp__claude-flow__swarm_status - Monitor progress

📊 Progress Format

📊 Progress Overview
├── Total: X | ✅ Complete: X | 🔄 Active: X | ⭕ Todo: X
└── Priority: 🔴 HIGH | 🟡 MEDIUM | 🟢 LOW

🎯 Performance Tips

  1. Batch Everything - Multiple operations = 1 message
  2. Parallel First - Think concurrent execution
  3. Memory is Key - Cross-agent coordination
  4. Monitor Progress - Real-time tracking
  5. Enable Hooks - Automated coordination

⚡ Quick Examples

Research Task

// Single message with all operations
mcp__claude-flow__swarm_init { topology: "mesh", maxAgents: 5 }
mcp__claude-flow__agent_spawn { type: "researcher" }
mcp__claude-flow__agent_spawn { type: "code-analyzer" }
mcp__claude-flow__task_orchestrate { task: "Research patterns" }

Development Task

// All todos in ONE call
TodoWrite { todos: [
  { id: "1", content: "Design API", status: "in_progress", priority: "high" },
  { id: "2", content: "Implement auth", status: "pending", priority: "high" },
  { id: "3", content: "Write tests", status: "pending", priority: "medium" },
  { id: "4", content: "Documentation", status: "pending", priority: "low" }
]}

🔗 Resources

Remember: Claude Flow coordinates, Claude Code creates!

  • Never save working files, text/mds and tests to the root folder.