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Self optimization

Skill a5c-ai/babysitter/library/methodologies/ruflo/skills/self-optimization

SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.From its SKILL.md

Install
npx -y skills add a5c-ai/babysitter --skill self-optimization

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.5 KB, 232 tokens by cl100k_base, as published. Nobody here has run it

  • Improving routing and agent selection over time
  • Adapting to new project patterns without forgetting old ones
  • Building cross-session intelligence

SONA Cycle

  1. Extract Patterns - Mine execution data for recurring patterns
  2. RETRIEVE - Search ReasoningBank for matching trajectories
  3. JUDGE - Evaluate trajectory applicability in current context
  4. DISTILL - Compress and store new entries
  5. Adapt - Update weights with EWC++ regularization

Anti-Forgetting (EWC++)

  • Elastic Weight Consolidation prevents overwriting previously learned patterns
  • Fisher information matrix tracks parameter importance
  • Configurable regularization penalty for new adaptations

RL Algorithms

Q-Learning, SARSA, PPO, DQN, A2C, TD3, SAC, DDPG, Rainbow

Agents Used

  • agents/optimizer/ - Performance tuning
  • agents/adaptive-queen/ - Real-time adaptation

Tool Use

Invoke via babysitter process: methodologies/ruflo/ruflo-intelligence

What ships with it: 1 file

229 B alongside SKILL.md

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