6ed69a3d48
Major changes: - Organized Python v1 implementation into v1/ subdirectory - Created Rust workspace with 9 modular crates: - wifi-densepose-core: Core types, traits, errors - wifi-densepose-signal: CSI processing, phase sanitization, FFT - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch) - wifi-densepose-api: Axum-based REST/WebSocket API - wifi-densepose-db: SQLx database layer - wifi-densepose-config: Configuration management - wifi-densepose-hardware: Hardware abstraction - wifi-densepose-wasm: WebAssembly bindings - wifi-densepose-cli: Command-line interface Documentation: - ADR-001: Workspace structure - ADR-002: Signal processing library selection - ADR-003: Neural network inference strategy - DDD domain model with bounded contexts Testing: - 69 tests passing across all crates - Signal processing: 45 tests - Neural networks: 21 tests - Core: 3 doc tests Performance targets: - 10x faster CSI processing (~0.5ms vs ~5ms) - 5x lower memory usage (~100MB vs ~500MB) - WASM support for browser deployment
132 lines
3.1 KiB
Markdown
132 lines
3.1 KiB
Markdown
# SPARC Orchestrator Mode
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## Purpose
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Multi-agent task orchestration with TodoWrite/TodoRead/Task/Memory using MCP tools.
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## Activation
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### Option 1: Using MCP Tools (Preferred in Claude Code)
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```javascript
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mcp__claude-flow__sparc_mode {
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mode: "orchestrator",
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task_description: "coordinate feature development"
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}
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```
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### Option 2: Using NPX CLI (Fallback when MCP not available)
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```bash
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# Use when running from terminal or MCP tools unavailable
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npx claude-flow sparc run orchestrator "coordinate feature development"
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# For alpha features
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npx claude-flow@alpha sparc run orchestrator "coordinate feature development"
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```
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### Option 3: Local Installation
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```bash
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# If claude-flow is installed locally
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./claude-flow sparc run orchestrator "coordinate feature development"
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```
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## Core Capabilities
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- Task decomposition
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- Agent coordination
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- Resource allocation
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- Progress tracking
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- Result synthesis
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## Integration Examples
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### Using MCP Tools (Preferred)
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```javascript
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// Initialize orchestration swarm
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mcp__claude-flow__swarm_init {
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topology: "hierarchical",
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strategy: "auto",
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maxAgents: 8
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}
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// Spawn coordinator agent
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mcp__claude-flow__agent_spawn {
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type: "coordinator",
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capabilities: ["task-planning", "resource-management"]
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}
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// Orchestrate tasks
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mcp__claude-flow__task_orchestrate {
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task: "feature development",
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strategy: "parallel",
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dependencies: ["auth", "ui", "api"]
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}
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```
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### Using NPX CLI (Fallback)
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```bash
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# Initialize orchestration swarm
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npx claude-flow swarm init --topology hierarchical --strategy auto --max-agents 8
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# Spawn coordinator agent
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npx claude-flow agent spawn --type coordinator --capabilities "task-planning,resource-management"
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# Orchestrate tasks
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npx claude-flow task orchestrate --task "feature development" --strategy parallel --deps "auth,ui,api"
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```
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## Orchestration Patterns
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- Hierarchical coordination
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- Parallel execution
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- Sequential pipelines
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- Event-driven flows
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- Adaptive strategies
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## Coordination Tools
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- TodoWrite for planning
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- Task for agent launch
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- Memory for sharing
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- Progress monitoring
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- Result aggregation
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## Workflow Example
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### Using MCP Tools (Preferred)
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```javascript
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// 1. Initialize orchestration swarm
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mcp__claude-flow__swarm_init {
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topology: "hierarchical",
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maxAgents: 10
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}
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// 2. Create workflow
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mcp__claude-flow__workflow_create {
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name: "feature-development",
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steps: ["design", "implement", "test", "deploy"]
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}
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// 3. Execute orchestration
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mcp__claude-flow__sparc_mode {
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mode: "orchestrator",
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options: {parallel: true, monitor: true},
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task_description: "develop user management system"
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}
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// 4. Monitor progress
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mcp__claude-flow__swarm_monitor {
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swarmId: "current",
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interval: 5000
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}
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```
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### Using NPX CLI (Fallback)
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```bash
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# 1. Initialize orchestration swarm
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npx claude-flow swarm init --topology hierarchical --max-agents 10
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# 2. Create workflow
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npx claude-flow workflow create --name "feature-development" --steps "design,implement,test,deploy"
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# 3. Execute orchestration
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npx claude-flow sparc run orchestrator "develop user management system" --parallel --monitor
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# 4. Monitor progress
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npx claude-flow swarm monitor --interval 5000
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``` |