wanshuiyin/Auto-claude-code-research-in-sleep

11,118 stars · Last commit 2026-06-01

ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.

README preview

# Auto-claude-code-research-in-sleep (ARIS ⚔️🌙)

<p align="center">
  <a href="https://huggingface.co/papers/2605.03042">
    <img src="docs/hf_daily_paper_1.svg" alt="Hugging Face Daily Paper · #1 Paper of the Day" width="360">
  </a>
</p>

[![Technical Report](https://img.shields.io/badge/Technical%20Report-arXiv%3A2605.03042-b31b1b?style=flat&logo=arxiv)](https://huggingface.co/papers/2605.03042) · [![ARIS Intro (HTML)](https://img.shields.io/badge/ARIS%20Intro-HTML%20%C2%B7%20by%20%2Frender--html-1a4a8c?style=flat&logo=html5&logoColor=white)](https://wanshuiyin.github.io/Auto-claude-code-research-in-sleep/ARIS_INTRO.html) · [![ARIS Intro Slides — VALSE 2026](https://img.shields.io/badge/Slides%20%40%20VALSE%202026-PDF%20%C2%B7%20by%20%2Fpaper--talk-EC1C24?style=flat&logo=adobeacrobatreader&logoColor=white)](docs/aris_intro_slides.pdf) · [![AI Agents](https://img.shields.io/badge/AI%20Agents-AGENT__GUIDE.md-4B2E83?style=flat&logo=readthedocs&logoColor=white)](AGENT_GUIDE.md) · [![Featured on PaperWeekly](https://img.shields.io/badge/Featured%20on-PaperWeekly-red?style=flat)](https://mp.weixin.qq.com/s/tDniVryVGjDkkkWl-5sTkQ) · [![Featured in awesome-agent-skills](https://img.shields.io/badge/Featured%20in-awesome--agent--skills-blue?style=flat&logo=github)](https://github.com/VoltAgent/awesome-agent-skills) · [![AI Digital Crew - Project of the Day](https://img.shields.io/badge/AI%20Digital%20Crew-Project%20of%20the%20Day%20(2026.03.14)-orange?style=flat)](https://aidigitalcrew.com) · [![GitHub stars](https://img.shields.io/github/stars/wanshuiyin/Auto-claude-code-research-in-sleep?style=flat&logo=github&logoColor=white&color=gold&label=Stars)](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/stargazers) · [💬 Join Community](#community) · [![Cite](https://img.shields.io/badge/📖_Cite_Us-BibTeX-green?style=flat)](#citation)

💡 *Use ARIS as a skill-based workflow in [Claude Code](https://docs.anthropic.com/en/docs/claude-code) / [Codex CLI](skills/skills-codex/) / [Cursor](docs/CURSOR_ADAPTATION.md) / [Trae](docs/TRAE_ARIS_RUNBOOK_EN.md) / [Antigravity](docs/ANTIGRAVITY_ADAPTATION.md) / [GitHub Copilot CLI](docs/COPILOT_CLI_ADAPTATION.md) / [OpenClaw](docs/OPENCLAW_ADAPTATION.md), or get the full experience with the standalone CLI — enjoy any way you like!*

🌱 *ARIS is a methodology, not a platform. What matters is the research workflow — take it wherever you go.*

🔥 *ARIS natively fits — and already supports — any agent's ultracode-style deep mode: its **breadth** pass adapts to whatever a runtime exposes — Claude Code's ultracode / dynamic workflows on Opus 4.8 (xhigh, or max effort if budget allows), Codex `spawn_agent` / equivalents, or another model entirely — degrading cleanly **parallel fan-out** → **agent spawn** → **plain sequential**.*
*ultracode supplies firepower to the breadth half ARIS always had, giving three clean roles: **depth → breadth**, **cross-model review → accuracy**, **research wiki → memory**.*
*However a loop is driven — ultracode breadth or goal-mode persistence — every loop reports to the same cross-model jury + research wiki: it can drive, never acquit.*

🤖 **AI agents:** Read [`AGENT_GUIDE.md`](AGENT_GUIDE.md) instead — structured for LLM consumption, not human browsing.

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