clawd
d81e403f01
COMPLETED TASKS: ✅ 06-01: Workout Swap System - Added swapped_from_id to workout_logs - Created workout_swaps table for history - POST /api/workouts/:id/swap endpoint - GET /api/workouts/available endpoint - Reversible swaps with audit trail ✅ 06-02: Muscle Group Recovery Tracking - Created muscle_group_recovery table - Implemented calculateRecoveryScore() function - GET /api/recovery/muscle-groups endpoint - GET /api/recovery/most-recovered endpoint - Auto-tracking on workout log completion ✅ 06-03: Smart Workout Recommendations - GET /api/recommendations/smart-workout endpoint - 7-day workout analysis algorithm - Recovery-based filtering (>30% threshold) - Top 3 recommendations with context - Context-aware reasoning messages DATABASE CHANGES: - Added 4 new tables: muscle_group_recovery, workout_swaps, custom_workouts, custom_workout_exercises - Extended workout_logs with: swapped_from_id, source_type, custom_workout_id, custom_workout_exercise_id - Created 7 new indexes for performance IMPLEMENTATION: - Recovery service with 4 core functions - 2 new route handlers (recovery, smartRecommendations) - Updated workouts router with swap endpoints - Integrated recovery tracking into POST /api/logs - Full error handling and logging TESTING: - Test file created: /backend/test/phase-06-tests.js - Ready for E2E and staging validation STATUS: Ready for frontend integration and production review Branch: feature/06-phase-06
59 lines
1.3 KiB
Markdown
59 lines
1.3 KiB
Markdown
# Performance Bottleneck Analysis
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## Purpose
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Identify and resolve performance bottlenecks in your development workflow.
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## Automated Analysis
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### 1. Real-time Detection
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The post-task hook automatically analyzes:
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- Execution time vs. complexity
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- Agent utilization rates
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- Resource constraints
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- Operation patterns
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### 2. Common Bottlenecks
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**Time Bottlenecks:**
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- Tasks taking > 5 minutes
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- Sequential operations that could parallelize
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- Redundant file operations
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**Coordination Bottlenecks:**
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- Single agent for complex tasks
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- Unbalanced agent workloads
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- Poor topology selection
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**Resource Bottlenecks:**
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- High operation count (> 100)
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- Memory constraints
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- I/O limitations
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### 3. Improvement Suggestions
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```
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Tool: mcp__claude-flow__task_results
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Parameters: {"taskId": "task-123", "format": "detailed"}
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Result includes:
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{
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"bottlenecks": [
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{
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"type": "coordination",
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"severity": "high",
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"description": "Single agent used for complex task",
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"recommendation": "Spawn specialized agents for parallel work"
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}
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],
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"improvements": [
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{
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"area": "execution_time",
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"suggestion": "Use parallel task execution",
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"expectedImprovement": "30-50% time reduction"
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}
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]
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}
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```
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## Continuous Optimization
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The system learns from each task to prevent future bottlenecks! |