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
26 lines
533 B
Markdown
26 lines
533 B
Markdown
# smart-spawn
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Intelligently spawn agents based on workload analysis.
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## Usage
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```bash
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npx claude-flow automation smart-spawn [options]
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```
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## Options
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- `--analyze` - Analyze before spawning
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- `--threshold <n>` - Spawn threshold
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- `--topology <type>` - Preferred topology
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## Examples
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```bash
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# Smart spawn with analysis
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npx claude-flow automation smart-spawn --analyze
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# Set spawn threshold
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npx claude-flow automation smart-spawn --threshold 5
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# Force topology
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npx claude-flow automation smart-spawn --topology hierarchical
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```
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