neural-train

Original：🇺🇸 English

Translated

Train SONA neural patterns from successful task completions, view learned patterns, and optimize the intelligence pipeline

4installs

Sourceruvnet/ruflo

Added on2026-04-30

NPX Install

npx skill4agent add ruvnet/ruflo neural-train

SKILL.md Content

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Neural Training

Train and manage SONA neural patterns for self-learning.

When to use

After completing a successful task, use this skill to capture what worked and train the intelligence system so future tasks benefit from learned patterns.

Steps

Check current neural status — call
```
mcp__claude-flow__neural_status
```
to see active patterns and training state

Start a trajectory — call

mcp__claude-flow__hooks_intelligence_trajectory-start

with the task context

Record steps — for each significant action, call

mcp__claude-flow__hooks_intelligence_trajectory-step

End trajectory — call
```
mcp__claude-flow__hooks_intelligence_trajectory-end
```
with outcome (success/failure)

Train patterns — call

mcp__claude-flow__neural_train

with

--pattern-type coordination --epochs 10

Store patterns — call

mcp__claude-flow__hooks_intelligence_pattern-store

to persist learnings

Verify — call
```
mcp__claude-flow__neural_patterns
```
to confirm patterns were stored

CLI alternative

bash

npx @claude-flow/cli@latest neural train --pattern-type coordination --epochs 10
npx @claude-flow/cli@latest neural patterns --list
npx @claude-flow/cli@latest neural status
npx @claude-flow/cli@latest hooks pretrain --model-type moe --epochs 10

SONA adaptation

For real-time micro-adaptation (<0.05ms), use:

```
mcp__claude-flow__ruvllm_sona_create
```
to initialize a SONA instance
```
mcp__claude-flow__ruvllm_sona_adapt
```
to adapt weights based on feedback