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slime

TOOL

LLM post-training framework for RL Scaling from THUDM. Supports SFT and RL training with multi-turn compilation feedback, powering projects like TritonForge for automated GPU kernel generation. Apache 2.0 licensed

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Overview

slime is a free tool on OpenRuna. LLM post-training framework for RL Scaling from THUDM. Supports SFT and RL training with multi-turn compilation feedback, powering projects like TritonForge for automated GPU kerne

What this tool does

Reach for "slime" whenever you need a reliable tool for real work across ChatGPT, Claude, Gemini, and Cursor. LLM post-training framework for RL Scaling from THUDM. Supports SFT and RL training with multi-turn compilation feedback, powering projects like TritonForge for automated GPU kernel generation. Apache 2.0 licensed On OpenRuna it sits inside a connected graph of related tools, tools, and datasets, so branching into adjacent resources is one click away. Paste it straight into a chat, drop it into a system prompt, or store it as a reusable skill.

Use cases

  • Fork it as a baseline and layer in your own project context, constraints, and examples.
  • Keep it in a shared library as the canonical version of this tool for your organisation.
  • Combine it with related tools and prompts in the same OpenRuna category to build an end-to-end workflow.
  • Reach for it during planning or review sessions when you want consistent, AI-assisted structure.

Example output

Ask the model to apply "slime" to your scenario and it returns a structured answer — clear sections, actionable steps, and assumptions stated upfront — ready to paste into docs, tickets, or code comments. Add one example of your own and the output quality jumps noticeably.

Tips by platform

Claude

In Claude, paste the full tool as your first message or add it to Project instructions, then ask Claude to confirm assumptions before it executes. For longer tools, iterate inside the artifact panel.

ChatGPT

ChatGPT responds well when you paste this tool and immediately give one concrete example of your input. Use a reasoning-capable model for multi-step work.

Cursor

Add this tool to your Cursor rules and invoke it from Agent mode for repeatable results. Link back to its OpenRuna page in the rule so the source stays discoverable.

Frequently asked questions

What is "slime"?
It is a tool listed on OpenRuna — LLM post-training framework for RL Scaling from THUDM. Supports SFT and RL training with multi-turn compilation feedback, powering projects like TritonForge for automated GPU kernel generation. Apache 2.0 licensed You can copy and adapt it for ChatGPT, Claude, Cursor, or any other AI assistant.
Is "slime" free to use?
Most OpenRuna resources are open or CC0-licensed. Check the license shown on this page before commercial use; premium collections are clearly marked as such.
How do I get the best results from this tool?
Replace any placeholders, add your project context, and ask the model to confirm its assumptions first. Iterate over 2–3 follow-up turns rather than expecting a perfect first response.
Does "slime" work with both Claude and ChatGPT?
Yes — it is model-agnostic text, so it runs on Claude, ChatGPT, Gemini, and Cursor. The tips on this page cover each of those assistants specifically.
Where can I find resources related to "slime"?
Scroll to the Related resources section on this page, or open the matching category hub on OpenRuna to find connected prompts, tools, agents, and datasets in the same topic area.

Related resources