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
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# Smart Agent Auto-Spawning
## Purpose
Automatically spawn the right agents at the right time without manual intervention.
## Auto-Spawning Triggers
### 1. File Type Detection
When editing files, agents auto-spawn:
- **JavaScript/TypeScript**: Coder agent
- **Markdown**: Researcher agent
- **JSON/YAML**: Analyst agent
- **Multiple files**: Coordinator agent
### 2. Task Complexity
```
Simple task: "Fix typo"
→ Single coordinator agent
Complex task: "Implement OAuth with Google"
→ Architect + Coder + Tester + Researcher
```
### 3. Dynamic Scaling
The system monitors workload and spawns additional agents when:
- Task queue grows
- Complexity increases
- Parallel opportunities exist
**Status Monitoring:**
```javascript
// Check swarm health
mcp__claude-flow__swarm_status({
"swarmId": "current"
})
// Monitor agent performance
mcp__claude-flow__agent_metrics({
"agentId": "agent-123"
})
```
## Configuration
### MCP Tool Integration
Uses Claude Flow MCP tools for agent coordination:
```javascript
// Initialize swarm with appropriate topology
mcp__claude-flow__swarm_init({
"topology": "mesh",
"maxAgents": 8,
"strategy": "auto"
})
// Spawn agents based on file type
mcp__claude-flow__agent_spawn({
"type": "coder",
"name": "JavaScript Handler",
"capabilities": ["javascript", "typescript"]
})
```
### Fallback Configuration
If MCP tools are unavailable:
```bash
npx claude-flow hook pre-task --auto-spawn-agents
```
## Benefits
- 🤖 Zero manual agent management
- 🎯 Perfect agent selection
- 📈 Dynamic scaling
- 💾 Resource efficiency