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
45 lines
1.0 KiB
Markdown
45 lines
1.0 KiB
Markdown
# Token Usage Optimization
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## Purpose
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Reduce token consumption while maintaining quality through intelligent coordination.
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## Optimization Strategies
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### 1. Smart Caching
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- Search results cached for 5 minutes
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- File content cached during session
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- Pattern recognition reduces redundant searches
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### 2. Efficient Coordination
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- Agents share context automatically
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- Avoid duplicate file reads
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- Batch related operations
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### 3. Measurement & Tracking
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```bash
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# Check token savings after session
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Tool: mcp__claude-flow__token_usage
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Parameters: {"operation": "session", "timeframe": "24h"}
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# Result shows:
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{
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"metrics": {
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"tokensSaved": 15420,
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"operations": 45,
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"efficiency": "343 tokens/operation"
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}
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}
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```
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## Best Practices
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1. **Use Task tool** for complex searches
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2. **Enable caching** in pre-search hooks
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3. **Batch operations** when possible
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4. **Review session summaries** for insights
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## Token Reduction Results
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- 📉 32.3% average token reduction
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- 🎯 More focused operations
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- 🔄 Intelligent result reuse
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- 📊 Cumulative improvements |