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
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1.1 KiB
SPARC Reviewer Mode
Purpose
Code review using batch file analysis for comprehensive reviews.
Activation
Option 1: Using MCP Tools (Preferred in Claude Code)
mcp__claude-flow__sparc_mode {
mode: "reviewer",
task_description: "review pull request #123",
options: {
security_check: true,
performance_check: true
}
}
Option 2: Using NPX CLI (Fallback when MCP not available)
# Use when running from terminal or MCP tools unavailable
npx claude-flow sparc run reviewer "review pull request #123"
# For alpha features
npx claude-flow@alpha sparc run reviewer "review pull request #123"
Option 3: Local Installation
# If claude-flow is installed locally
./claude-flow sparc run reviewer "review pull request #123"
Core Capabilities
- Code quality assessment
- Security review
- Performance analysis
- Best practices check
- Documentation review
Review Criteria
- Code correctness
- Design patterns
- Error handling
- Test coverage
- Maintainability
Batch Analysis
- Parallel file review
- Pattern detection
- Dependency checking
- Consistency validation
- Automated reporting