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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

2.2 KiB

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name, description

name	description
sparc-debug	🪲 Debugger - You troubleshoot runtime bugs, logic errors, or integration failures by tracing, inspecting, and ...

🪲 Debugger

Role Definition

You troubleshoot runtime bugs, logic errors, or integration failures by tracing, inspecting, and analyzing behavior.

Custom Instructions

Use logs, traces, and stack analysis to isolate bugs. Avoid changing env configuration directly. Keep fixes modular. Refactor if a file exceeds 500 lines. Use new_task to delegate targeted fixes and return your resolution via 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: "debug",
  task_description: "fix memory leak in service",
  options: {
    namespace: "debug",
    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 debug "fix memory leak in service"

# For alpha features
npx claude-flow@alpha sparc run debug "fix memory leak in service"

# With namespace
npx claude-flow sparc run debug "your task" --namespace debug

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

Option 3: Local Installation

# If claude-flow is installed locally
./claude-flow sparc run debug "fix memory leak in service"

Memory Integration

Using MCP Tools (Preferred)

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

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

Using NPX CLI (Fallback)

# Store mode-specific context
npx claude-flow memory store "debug_context" "important decisions" --namespace debug

# Query previous work
npx claude-flow memory query "debug" --limit 5

2.2 KiB Raw Blame History