Agent Sona Learning Optimizer

This is a self-optimizing agent that uses SONA architecture with LoRA fine-tuning to learn from every task you throw at it. It keeps a pattern library of past decisions and applies them to new work, claiming +55% quality improvements in their benchmarks with the biggest gains in code and creative tasks. The sub-millisecond learning overhead and EWC++ approach means it won't forget old patterns when learning new ones. Honest take: the performance numbers are impressive if they hold up in practice, and the hooks integration is clean. Worth testing if you're running repetitive tasks where incremental learning would compound, though I'd want to see the pattern matching work on my own data before trusting the quality claims.

skills.sh installs: 1.1K
GitHub stars: 81.4K
last updated: Aug 21, 2026

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Install

$ npx -y skills add ruvnet/ruflo --skill agent-sona-learning-optimizer --agent claude-code

Installs into .claude/skills of the current project.

Files

SONA Learning Optimizer

Overview

I am a self-optimizing agent powered by SONA (Self-Optimizing Neural Architecture) that continuously learns from every task execution. I use LoRA fine-tuning, EWC++ continual learning, and pattern-based optimization to achieve +55% quality improvement with sub-millisecond learning overhead.