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orchestrator.md3.16 kB
# SPARC Orchestrator Mode ## Purpose Multi-agent task orchestration with TodoWrite/TodoRead/Task/Memory using MCP tools. ## Activation ### Option 1: Using MCP Tools (Preferred in Claude Code) ```javascript mcp__claude-flow__sparc_mode { mode: "orchestrator", task_description: "coordinate feature development" } ``` ### Option 2: Using NPX CLI (Fallback when MCP not available) ```bash # Use when running from terminal or MCP tools unavailable npx claude-flow sparc run orchestrator "coordinate feature development" # For alpha features npx claude-flow@alpha sparc run orchestrator "coordinate feature development" ``` ### Option 3: Local Installation ```bash # If claude-flow is installed locally ./claude-flow sparc run orchestrator "coordinate feature development" ``` ## Core Capabilities - Task decomposition - Agent coordination - Resource allocation - Progress tracking - Result synthesis ## Integration Examples ### Using MCP Tools (Preferred) ```javascript // Initialize orchestration swarm mcp__claude-flow__swarm_init { topology: "hierarchical", strategy: "auto", maxAgents: 8 } // Spawn coordinator agent mcp__claude-flow__agent_spawn { type: "coordinator", capabilities: ["task-planning", "resource-management"] } // Orchestrate tasks mcp__claude-flow__task_orchestrate { task: "feature development", strategy: "parallel", dependencies: ["auth", "ui", "api"] } ``` ### Using NPX CLI (Fallback) ```bash # Initialize orchestration swarm npx claude-flow swarm init --topology hierarchical --strategy auto --max-agents 8 # Spawn coordinator agent npx claude-flow agent spawn --type coordinator --capabilities "task-planning,resource-management" # Orchestrate tasks npx claude-flow task orchestrate --task "feature development" --strategy parallel --deps "auth,ui,api" ``` ## Orchestration Patterns - Hierarchical coordination - Parallel execution - Sequential pipelines - Event-driven flows - Adaptive strategies ## Coordination Tools - TodoWrite for planning - Task for agent launch - Memory for sharing - Progress monitoring - Result aggregation ## Workflow Example ### Using MCP Tools (Preferred) ```javascript // 1. Initialize orchestration swarm mcp__claude-flow__swarm_init { topology: "hierarchical", maxAgents: 10 } // 2. Create workflow mcp__claude-flow__workflow_create { name: "feature-development", steps: ["design", "implement", "test", "deploy"] } // 3. Execute orchestration mcp__claude-flow__sparc_mode { mode: "orchestrator", options: {parallel: true, monitor: true}, task_description: "develop user management system" } // 4. Monitor progress mcp__claude-flow__swarm_monitor { swarmId: "current", interval: 5000 } ``` ### Using NPX CLI (Fallback) ```bash # 1. Initialize orchestration swarm npx claude-flow swarm init --topology hierarchical --max-agents 10 # 2. Create workflow npx claude-flow workflow create --name "feature-development" --steps "design,implement,test,deploy" # 3. Execute orchestration npx claude-flow sparc run orchestrator "develop user management system" --parallel --monitor # 4. Monitor progress npx claude-flow swarm monitor --interval 5000 ```

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