orchestra-research/ai-research-skills

This repository is a collection of 98 add-on modules, called skills, that you can install into AI coding agents like Claude Code, Cursor, or Gemini CLI to give them deep expertise in machine learning research tools and workflows. The goal is to let an AI agent handle the full lifecycle of an AI research project: finding ideas, running experiments, and writing a paper, without the human having to guide each step. The skills are organized into 23 categories covering the main areas of modern AI research work. Categories include fine-tuning language models, training models across multiple machines, making models faster for deployment, building retrieval systems, working with multimodal data like images and audio, ensuring model safety, and writing academic papers with LaTeX. Each skill is documented with real code examples and practical guides for a specific framework, such as vLLM for fast inference, DeepSpeed for distributed training, or TRL for reinforcement learning from human feedback. A special skill called autoresearch sits at the top and acts as a coordinator. When you give an agent a research question, autoresearch figures out which sub-skills to call and in what order, routing through literature review, experimentation, and paper writing as needed. Installation is done via a one-line command using npx, or through the Claude Code plugin marketplace if you use that tool. The installer detects which AI agents you have installed and puts the skills where each agent can find them. You can install all 98 at once, pick a category bundle, or install individual skills. The project is maintained by Orchestra Research and is licensed under MIT. The full README is longer than what was shown.