Agent Skills: Neural Training Skill

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

npx claude-flow neural train --model-type moe --epochs 10

Check Status

npx claude-flow neural status

View Patterns

npx claude-flow neural patterns --type all

Predict

npx claude-flow neural predict --input "task description"

Optimize

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