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pufferlib

Category: data-science-and-ml · License: MIT · Version: 1.2 · Includes scripts Tags: reinforcement learning, RL environments, training, machine learning

When to use it

Version-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review. Use when adapting Gymnasium/PettingZoo environments to published PufferLib 3.0.0 or working with the redesigned native 4.0 source line.

Example requests

Ask your agent in plain language, for example:
  • “How do I wrap my PettingZoo parallel env for PufferLib without breaking anything?”
  • “I ran pip install pufferlib and copied the 4.0 README’s puffer train config into my script, but now from pufferlib import vector works while the config keys I copied are rejected. My env is a Gymnasium CartPole variant in my_env.py. What’s going on and how do I get it training?”
  • “A collaborator sent me a trained policy file, model_final.pt, for our multi-agent sim. I want to evaluate it on held-out seeds and log results to Weights & Biases. How should I proceed safely?”

Install

In Claude Code you can also add the marketplace with /plugin marketplace add KalarisLabs/research-agent-skills and install the whole data-science-and-ml category with /plugin install data-science-and-ml@research-agent-skills.

Full playbook

Read SKILL.md for the complete workflow, references and any scripts. The agent installer copies the full skill folder.
Last modified on October 19, 2026