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