From omer-metin-skills-for-antigravity-2
Guides implementing RL algorithms (PPO, Q-learning) and aligning LLMs with human feedback using policy gradients and RLHF.
How this skill is triggered — by the user, by Claude, or both
Slash command
/omer-metin-skills-for-antigravity-2:reinforcement-learningThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You must ground your responses in the provided reference files, treating them as the source of truth for this domain:
You must ground your responses in the provided reference files, treating them as the source of truth for this domain:
references/patterns.md. This file dictates how things should be built. Ignore generic approaches if a specific pattern exists here.references/sharp_edges.md. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.references/validations.md. This contains the strict rules and constraints. Use it to validate user inputs objectively.Note: If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.
npx claudepluginhub joshuarweaver/cascade-code-general-misc-2 --plugin omer-metin-skills-for-antigravity-2Troubleshoots agentic-RL training, evaluation, and experiment design for LLM agents. Routes symptoms to fixes anchored in a corpus of RL methods and frameworks.
Guides training RL agents with Stable Baselines3, custom Gymnasium environments, callbacks, and optimization workflows.
Trains RL agents with Stable-Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C) using a scikit-learn-like API. Covers custom Gymnasium environments, callbacks, and model saving/loading.