Auto-claude-code-research-in-sleep
ARIS is a lightweight Markdown skill tool for autonomous machine learning research.
- Region
- Domestic
- Pricing
- Free
- Open source
- Yes
- GitHub Stars
- ★ 11.4k
- Source
- GitHub
- Added
- 2026-06-05
- Last verified
- 2026-06-05
Overview
ARIS is a lightweight Markdown skill tool designed specifically for autonomous machine learning research. It enhances researcher efficiency through features like cross-model review loops, idea discovery, and experiment automation. It requires no specific framework or platform and can be used with any LLM agent, such as Claude Code, Codex, OpenClaw, and more.
Key features
- ▪Lightweight Markdown skills
- ▪Cross-model review loops
- ▪Idea discovery
- ▪Experiment automation
- ▪No framework constraints
Use cases
Pros
- ＋Supports multiple LLM agents
- ＋Flexible research workflow
- ＋Easy to integrate and use
Limitations / notes
- －Requires some technical background
- －May not suit all research domains
Who it's for
This overview was compiled by AI from public sources and may contain inaccuracies — please refer to the official site.
FAQ
No, ARIS does not require a specific framework and can work with various LLM agents.
No, ARIS does not require a specific framework and can work with various LLM agents.
ARIS is suitable for a wide range of research scenarios, including machine learning, investment due diligence, legal research, and more.
ARIS is suitable for a wide range of research scenarios, including machine learning, investment due diligence, legal research, and more.
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