Files

Claude 6ed69a3d48 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

2026-01-13 03:11:16 +00:00

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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:

// 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:

// 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:

npx claude-flow hook pre-task --auto-spawn-agents

Benefits

🤖 Zero manual agent management
🎯 Perfect agent selection
📈 Dynamic scaling
💾 Resource efficiency

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