claude-flow/.claude/commands/training/neural-patterns.md

Enterprise-grade AI agent orchestration with ruv-swarm integration (Alpha Release)

# Neural Pattern Training

## Purpose
Continuously improve coordination through neural network learning.

## How Training Works

### 1. Automatic Learning
Every successful operation trains the neural networks:
- Edit patterns for different file types
- Search strategies that find results faster
- Task decomposition approaches
- Agent coordination patterns

### 2. Manual Training
```
Tool: mcp__claude-flow__neural_train
Parameters: {"iterations": 20}
```

### 3. Pattern Types

**Cognitive Patterns:**
- Convergent: Focused problem-solving
- Divergent: Creative exploration
- Lateral: Alternative approaches
- Systems: Holistic thinking
- Critical: Analytical evaluation
- Abstract: High-level design

### 4. Improvement Tracking
```
Tool: mcp__claude-flow__neural_status
Result: {
  "patterns": {
    "convergent": 0.92,
    "divergent": 0.87,
    "lateral": 0.85
  },
  "improvement": "5.3% since last session",
  "confidence": 0.89
}
```

## Benefits
- 🧠 Learns your coding style
- 📈 Improves with each use
- 🎯 Better task predictions
- ⚡ Faster coordination