neural-training
Neural pattern training with SONA (Self-Optimizing Neural Architecture), MoE (Mixture of Experts), and EWC++ for knowledge consolidation. Use when: pattern learning, model optimization, knowledge transfer, adaptive routing. Skip when: simple tasks, no learning required, one-off operations.
Profile →npx skills add ruvnet/ruflo --skill neural-training --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 Practi
- Purpose
- When to Trigger
- Intelligence Pipeline
- Components
- Commands
- Train Patterns
- Check Status
- View Patterns
- Predict
- Optimize
- Best Practices
npx claude-flow neural train --model-type moe --epochs 10 npx claude-flow neural status npx claude-flow neural patterns --type all npx claude-flow neural predict --input "task description" npx claude-flow neural optimize --target latency
What does the neural-training skill do?
Neural pattern training with SONA (Self-Optimizing Neural Architecture), MoE (Mixture of Experts), and EWC++ for knowledge consolidation. Use when: pattern learning, model optimization, knowledge transfer, adaptive routing. Skip when: simple tasks, no learning required, one-off operations.
How do I install it?
Run `npx skills add ruvnet/ruflo --skill neural-training --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ruvnet/ruflo, a repository with 67,015 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.