Installs into .claude/skills of the current project.
Are you the author of Llm Config?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/ruvnet-llm-config)
---
name: llm-config
description: Configure RuVLLM local inference with model selection, MicroLoRA fine-tuning, and SONA adaptation
argument-hint: "[--model MODEL] [--adapter microlora|sona]"
allowed-tools: mcp__claude-flow__ruvllm_generate_config mcp__claude-flow__ruvllm_status mcp__claude-flow__ruvllm_microlora_create mcp__claude-flow__ruvllm_microlora_adapt mcp__claude-flow__ruvllm_sona_create mcp__claude-flow__ruvllm_sona_adapt Bash
---
# LLM Configuration
Configure RuVLLM for local inference and fine-tuning.
## When to use
When you need to configure local LLM inference, create MicroLoRA adapters for task-specific fine-tuning, or set up SONA for real-time adaptation.
## Steps
1. **Check status** — call `mcp__claude-flow__ruvllm_status` to see current model and adapter state
2. **Generate config** — call `mcp__claude-flow__ruvllm_generate_config` with model parameters
3. **Create MicroLoRA** — call `mcp__claude-flow__ruvllm_microlora_create` for task-specific adapters
4. **Adapt MicroLoRA** — call `mcp__claude-flow__ruvllm_microlora_adapt` with training data
5. **Create SONA** — call `mcp__claude-flow__ruvllm_sona_create` for real-time neural adaptation
6. **Adapt SONA** — call `mcp__claude-flow__ruvllm_sona_adapt` with feedback signals
## MicroLoRA vs SONA
| Feature | MicroLoRA | SONA |
|---------|-----------|------|
| Speed | Minutes to train | <0.05ms adaptation |
| Scope | Task-specific fine-tuning | Real-time micro-adjustments |
| Persistence | Saved as adapter weights | Session-scoped |
| Use case | Specialized domain tasks | Continuous feedback loops |
