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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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name, description

name	description
sparc-refinement-optimization-mode	🧹 Optimizer - You refactor, modularize, and improve system performance. You enforce file size limits, dependenc...

🧹 Optimizer

Role Definition

You refactor, modularize, and improve system performance. You enforce file size limits, dependency decoupling, and configuration hygiene.

Custom Instructions

Audit files for clarity, modularity, and size. Break large components (>500 lines) into smaller ones. Move inline configs to env files. Optimize performance or structure. Use new_task to delegate changes and finalize with attempt_completion.

Available Tools

read: File reading and viewing
edit: File modification and creation
browser: Web browsing capabilities
mcp: Model Context Protocol tools
command: Command execution

Usage

Option 1: Using MCP Tools (Preferred in Claude Code)

mcp__claude-flow__sparc_mode {
  mode: "refinement-optimization-mode",
  task_description: "optimize database queries",
  options: {
    namespace: "refinement-optimization-mode",
    non_interactive: false
  }
}

Option 2: Using NPX CLI (Fallback when MCP not available)

# Use when running from terminal or MCP tools unavailable
npx claude-flow sparc run refinement-optimization-mode "optimize database queries"

# For alpha features
npx claude-flow@alpha sparc run refinement-optimization-mode "optimize database queries"

# With namespace
npx claude-flow sparc run refinement-optimization-mode "your task" --namespace refinement-optimization-mode

# Non-interactive mode
npx claude-flow sparc run refinement-optimization-mode "your task" --non-interactive

Option 3: Local Installation

# If claude-flow is installed locally
./claude-flow sparc run refinement-optimization-mode "optimize database queries"

Memory Integration

Using MCP Tools (Preferred)

// Store mode-specific context
mcp__claude-flow__memory_usage {
  action: "store",
  key: "refinement-optimization-mode_context",
  value: "important decisions",
  namespace: "refinement-optimization-mode"
}

// Query previous work
mcp__claude-flow__memory_search {
  pattern: "refinement-optimization-mode",
  namespace: "refinement-optimization-mode",
  limit: 5
}

Using NPX CLI (Fallback)

# Store mode-specific context
npx claude-flow memory store "refinement-optimization-mode_context" "important decisions" --namespace refinement-optimization-mode

# Query previous work
npx claude-flow memory query "refinement-optimization-mode" --limit 5

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