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
54 lines
1.3 KiB
Markdown
54 lines
1.3 KiB
Markdown
# SPARC Architect Mode
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## Purpose
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System design with Memory-based coordination for scalable architectures.
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## Activation
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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: "architect",
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task_description: "design microservices architecture",
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options: {
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detailed: true,
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memory_enabled: true
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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 architect "design microservices architecture"
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# For alpha features
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npx claude-flow@alpha sparc run architect "design microservices architecture"
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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 architect "design microservices architecture"
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```
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## Core Capabilities
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- System architecture design
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- Component interface definition
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- Database schema design
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- API contract specification
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- Infrastructure planning
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## Memory Integration
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- Store architecture decisions in Memory
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- Share component specifications across agents
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- Maintain design consistency
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- Track architectural evolution
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## Design Patterns
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- Microservices
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- Event-driven architecture
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- Domain-driven design
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- Hexagonal architecture
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- CQRS and Event Sourcing
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