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