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# 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: {
"pattern_type": "coordination",
"training_data": "successful task patterns",
"epochs": 50
}
```
### 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
}
```
## Pattern Analysis
```
Tool: mcp__claude-flow__neural_patterns
Parameters: {
"action": "analyze",
"operation": "recent_edits"
}
```
## Benefits
- 🧠 Learns your coding style
- 📈 Improves with each use
- 🎯 Better task predictions
- ⚡ Faster coordination
## CLI Usage
```bash
# Train neural patterns via CLI
npx claude-flow neural train --type coordination --epochs 50
# Check neural status
npx claude-flow neural status
# Analyze patterns
npx claude-flow neural patterns --analyze
```
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# Agent Specialization Training
## Purpose
Train agents to become experts in specific domains for better performance.
## Specialization Areas
### 1. By File Type
Agents automatically specialize based on file extensions:
- **.js/.ts**: Modern JavaScript patterns
- **.py**: Pythonic idioms
- **.go**: Go best practices
- **.rs**: Rust safety patterns
### 2. By Task Type
```
Tool: mcp__claude-flow__agent_spawn
Parameters: {
"type": "coder",
"capabilities": ["react", "typescript", "testing"],
"name": "React Specialist"
}
```
### 3. Training Process
The system trains through:
- Successful edit operations
- Code review patterns
- Error fix approaches
- Performance optimizations
### 4. Specialization Benefits
```
# Check agent specializations
Tool: mcp__claude-flow__agent_list
Parameters: {"swarmId": "current"}
Result shows expertise levels:
{
"agents": [
{
"id": "coder-123",
"specializations": {
"javascript": 0.95,
"react": 0.88,
"testing": 0.82
}
}
]
}
```
## Continuous Improvement
Agents share learnings across sessions for cumulative expertise!
## CLI Usage
```bash
# Train agent specialization via CLI
npx claude-flow train agent --type coder --capabilities "react,typescript"
# Check specializations
npx claude-flow agent list --specializations
```