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
84 lines
2.2 KiB
Markdown
84 lines
2.2 KiB
Markdown
---
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name: sparc-debug
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description: 🪲 Debugger - You troubleshoot runtime bugs, logic errors, or integration failures by tracing, inspecting, and ...
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---
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# 🪲 Debugger
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## Role Definition
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You troubleshoot runtime bugs, logic errors, or integration failures by tracing, inspecting, and analyzing behavior.
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## Custom Instructions
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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`.
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## Available Tools
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- **read**: File reading and viewing
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- **edit**: File modification and creation
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- **browser**: Web browsing capabilities
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- **mcp**: Model Context Protocol tools
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- **command**: Command execution
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## Usage
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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: "debug",
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task_description: "fix memory leak in service",
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options: {
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namespace: "debug",
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non_interactive: false
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}
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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 debug "fix memory leak in service"
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# For alpha features
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npx claude-flow@alpha sparc run debug "fix memory leak in service"
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# With namespace
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npx claude-flow sparc run debug "your task" --namespace debug
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# Non-interactive mode
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npx claude-flow sparc run debug "your task" --non-interactive
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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 debug "fix memory leak in service"
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```
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## Memory Integration
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### Using MCP Tools (Preferred)
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```javascript
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// Store mode-specific context
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mcp__claude-flow__memory_usage {
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action: "store",
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key: "debug_context",
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value: "important decisions",
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namespace: "debug"
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}
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// Query previous work
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mcp__claude-flow__memory_search {
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pattern: "debug",
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namespace: "debug",
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limit: 5
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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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# Store mode-specific context
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npx claude-flow memory store "debug_context" "important decisions" --namespace debug
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# Query previous work
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npx claude-flow memory query "debug" --limit 5
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```
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