claudegoodies
Skill

neural-training

From ruvnet

>

Facts

Repository
ruvnet/ruflo
Status
Actively maintained
Last commit
Source file
.agents/skills/neural-training/SKILL.md

Source preview

The instructions Claude Code reads when this skill runs.

# Neural Training Skill

## Purpose
Train and optimize neural patterns using SONA, MoE, and EWC++ systems.

## When to Trigger
- Training new patterns
- Optimizing agent routing
- Knowledge consolidation
- Pattern recognition tasks

## Intelligence Pipeline

1. **RETRIEVE** — Fetch relevant patterns via HNSW (150x-12,500x faster)
2. **JUDGE** — Evaluate with verdicts (success$failure)
3. **DISTILL** — Extract key learnings via LoRA
4. **CONSOLIDATE** — Prevent catastrophic forgetting via EWC++

## Components

| Component | Purpose | Performance |
|-----------|---------|-------------|
| SONA | Self-optimizing adaptation | <0.05ms |
| MoE | Expert routing | 8 experts |
| HNSW | Pattern search | 150x-12,500x |
| EWC++ | Prevent forgetting | Continuous |
| Flash Attention | Speed | 2.49x-7.47x |

## Commands

### Train Patterns
```bash
npx claude-flow neural train --model-type moe --epochs 10
```

### Check Status
```bash
npx claude-flow neural status
```

### View Patterns
```bash
npx claude-flow neural patterns --type all
```

### Predict
```bash
npx claude-flow neural predict --input "task description"
```

### Optimize
```bash
npx claude-flow neural optimize --target latency
```

## Best Practices
1. Use pretrain hook for batch learning
2. Store successful patterns after completion
3. Consolidate regularly to prevent forgetting
4. Route based on task complexity
View full source on GitHub →

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