Orchestra-Research/AI-research-SKILLs
Open-source skills library for autonomous AI research agents.
View on GitHub Updated 2026-06-16
What is Orchestra-Research/AI-research-SKILLs?
Orchestra-Research/AI-research-SKILLs is a comprehensive collection of 98 production-ready skills designed specifically for AI agents. It covers 23 categories including model architecture, fine-tuning, distributed training, safety, multimodal work, and mechanistic interpretability. The library supplies both high-level workflow orchestration and granular, framework-specific guidance drawn from official documentation and real-world usage.
The core autoresearch skill manages a two-loop system that routes tasks to the appropriate domain skills as needed. Each individual skill includes code examples, troubleshooting steps, and workflows tested in actual research and production environments. Installation works through an interactive command that detects supported coding agents and sets up the full set of skills with proper symlinks.
It targets AI researchers, agent developers, and teams building autonomous research systems who need reliable, expert-level assistance across the entire AI experimentation pipeline.
What you can build with Orchestra-Research/AI-research-SKILLs
End-to-end paper generation
An agent surveys recent literature, generates novel ideas, runs experiments using training and evaluation skills, then produces a complete draft paper.
Specialized model optimization
Agents apply post-training, quantization, and inference skills to improve model performance on specific hardware or latency targets.
Safety and alignment experiments
Researchers direct agents to test alignment techniques, run evaluations, and document findings using the dedicated safety skills.
Install Orchestra-Research/AI-research-SKILLs
Install
npx @orchestra-research/ai-research-skillsQuick start
npx @orchestra-research/ai-research-skills- 1Run the interactive installer with npx @orchestra-research/ai-research-skills
- 2Select your coding agent from the detected options during setup
- 3Allow the installer to place skills in ~/.orchestra/skills/ with symlinks
- 4Open the welcome documentation and instruct your agent to load the skills
- 5Start a research task by referencing the autoresearch orchestration layer
Orchestra-Research/AI-research-SKILLs: pros & cons
Pros
- +Broad coverage across 23 research categories with expert-level detail
- +Open-source and MIT licensed with community support channels
- +Includes both orchestration and low-level engineering skills
- +Installer automatically configures multiple popular coding agents
Cons
- –Requires compatible coding agents for full functionality
- –Large skill set may need initial configuration time
- –Focuses primarily on AI research rather than general tasks
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Frequently asked questions
The library contains 98 skills organized into 23 categories covering the complete AI research workflow.
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