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
113 lines
2.2 KiB
Markdown
113 lines
2.2 KiB
Markdown
# hook post-task
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Execute post-task cleanup, performance analysis, and memory storage.
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## Usage
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```bash
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npx claude-flow hook post-task [options]
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```
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## Options
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- `--task-id, -t <id>` - Task identifier for tracking
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- `--analyze-performance` - Generate performance metrics (default: true)
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- `--store-decisions` - Save task decisions to memory
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- `--export-learnings` - Export neural pattern learnings
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- `--generate-report` - Create task completion report
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## Examples
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### Basic post-task hook
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```bash
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npx claude-flow hook post-task --task-id "auth-implementation"
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```
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### With full analysis
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```bash
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npx claude-flow hook post-task -t "api-refactor" --analyze-performance --generate-report
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```
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### Memory storage
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```bash
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npx claude-flow hook post-task -t "bug-fix-123" --store-decisions --export-learnings
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```
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### Quick cleanup
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```bash
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npx claude-flow hook post-task -t "minor-update" --analyze-performance false
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```
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## Features
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### Performance Analysis
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- Measures execution time
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- Tracks token usage
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- Identifies bottlenecks
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- Suggests optimizations
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### Decision Storage
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- Saves key decisions made
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- Records implementation choices
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- Stores error resolutions
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- Maintains knowledge base
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### Neural Learning
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- Exports successful patterns
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- Updates coordination models
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- Improves future performance
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- Trains on task outcomes
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### Report Generation
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- Creates completion summary
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- Documents changes made
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- Lists files modified
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- Tracks metrics achieved
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## Integration
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This hook is automatically called by Claude Code when:
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- Completing a task
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- Switching to a new task
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- Ending a work session
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- After major milestones
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Manual usage in agents:
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```bash
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# In agent coordination
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npx claude-flow hook post-task --task-id "your-task-id" --analyze-performance true
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```
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## Output
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Returns JSON with:
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```json
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{
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"taskId": "auth-implementation",
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"duration": 1800000,
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"tokensUsed": 45000,
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"filesModified": 12,
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"performanceScore": 0.92,
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"learningsExported": true,
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"reportPath": "/reports/task-auth-implementation.md"
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}
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```
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## See Also
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- `hook pre-task` - Pre-task setup
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- `performance report` - Detailed metrics
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- `memory usage` - Memory management
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- `neural patterns` - Pattern analysis
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