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gravl/.claude/commands/analysis/performance-bottlenecks.md
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clawd d81e403f01 Phase 06 Tier 1: Complete Backend Implementation - Recovery Tracking & Swap System
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
2026-03-06 20:54:03 +01:00

1.3 KiB

Performance Bottleneck Analysis

Purpose

Identify and resolve performance bottlenecks in your development workflow.

Automated Analysis

1. Real-time Detection

The post-task hook automatically analyzes:

  • Execution time vs. complexity
  • Agent utilization rates
  • Resource constraints
  • Operation patterns

2. Common Bottlenecks

Time Bottlenecks:

  • Tasks taking > 5 minutes
  • Sequential operations that could parallelize
  • Redundant file operations

Coordination Bottlenecks:

  • Single agent for complex tasks
  • Unbalanced agent workloads
  • Poor topology selection

Resource Bottlenecks:

  • High operation count (> 100)
  • Memory constraints
  • I/O limitations

3. Improvement Suggestions

Tool: mcp__claude-flow__task_results
Parameters: {"taskId": "task-123", "format": "detailed"}

Result includes:
{
  "bottlenecks": [
    {
      "type": "coordination",
      "severity": "high",
      "description": "Single agent used for complex task",
      "recommendation": "Spawn specialized agents for parallel work"
    }
  ],
  "improvements": [
    {
      "area": "execution_time",
      "suggestion": "Use parallel task execution",
      "expectedImprovement": "30-50% time reduction"
    }
  ]
}

Continuous Optimization

The system learns from each task to prevent future bottlenecks!