feat: Complete Rust port of WiFi-DensePose with modular crates

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

.claude/commands/automation/smart-agents.md

@@ -0,0 +1,73 @@
+# Smart Agent Auto-Spawning
+
+## Purpose
+Automatically spawn the right agents at the right time without manual intervention.
+
+## Auto-Spawning Triggers
+
+### 1. File Type Detection
+When editing files, agents auto-spawn:
+- **JavaScript/TypeScript**: Coder agent
+- **Markdown**: Researcher agent
+- **JSON/YAML**: Analyst agent
+- **Multiple files**: Coordinator agent
+
+### 2. Task Complexity
+```
+Simple task: "Fix typo"
+→ Single coordinator agent
+
+Complex task: "Implement OAuth with Google"
+→ Architect + Coder + Tester + Researcher
+```
+
+### 3. Dynamic Scaling
+The system monitors workload and spawns additional agents when:
+- Task queue grows
+- Complexity increases
+- Parallel opportunities exist
+
+**Status Monitoring:**
+```javascript
+// Check swarm health
+mcp__claude-flow__swarm_status({
+  "swarmId": "current"
+})
+
+// Monitor agent performance
+mcp__claude-flow__agent_metrics({
+  "agentId": "agent-123"
+})
+```
+
+## Configuration
+
+### MCP Tool Integration
+Uses Claude Flow MCP tools for agent coordination:
+```javascript
+// Initialize swarm with appropriate topology
+mcp__claude-flow__swarm_init({
+  "topology": "mesh",
+  "maxAgents": 8,
+  "strategy": "auto"
+})
+
+// Spawn agents based on file type
+mcp__claude-flow__agent_spawn({
+  "type": "coder",
+  "name": "JavaScript Handler",
+  "capabilities": ["javascript", "typescript"]
+})
+```
+
+### Fallback Configuration
+If MCP tools are unavailable:
+```bash
+npx claude-flow hook pre-task --auto-spawn-agents
+```
+
+## Benefits
+- 🤖 Zero manual agent management
+- 🎯 Perfect agent selection
+- 📈 Dynamic scaling
+- 💾 Resource efficiency