{"repo":"wanshuiyin/Auto-claude-code-research-in-sleep","free":true,"listed":false,"github":"https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep","clone":"git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git","description":"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.","language":"Python","stars":14761,"topics":["ai-research","ai-tools","aris","autonomous-agent","claude","claude-code","claude-code-skills","codex","deep-learning","gpt","idea-generation","llm","machine-learning","mcp","mcp-server","ml-research","openai","paper-review","paper-writing","research-automation"],"license":"MIT","category":"ai_research_agent","readme_excerpt":"# Auto-claude-code-research-in-sleep (ARIS ⚔️🌙)\n\n

\n \n \"Hugging\n \n

\n\n[![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)\n\n💡 *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 **[ARIS-Code](docs/ARIS-Code-README_EN.md)** CLI — enjoy any way you like!*\n\n🌱 *ARIS is a methodology, not a platform. What matters is the research workflow — take it wherever you go.*\n\n🤖 **AI agents:** Read [`AGENT_GUIDE.md`](AGENT_GUIDE.md) instead — structured for LLM consumption, not human browsing.\n\n🛡️ **ARIS audits its own output → now [Anti-Autoresearch](https://github.com/wanshuiyin/Anti-Autoresearch) audits everyone's.** 61 signals — 46 integrity hack-patterns in 8 families, 13 AI-style impressions, 2 advisory — checked end-to-end into a deterministic, reviewer-ready report.\n*Self-consistency + fabrication forensics, **not** an AI-text detector.*\n\n

The field has put up with unreliable autoresearch long enough —
Anti-Autoresearch is the read that finally catches it.

\n\n🧱 **ARIS's reviewer is good — and it also proposed hashes nobody reads → [HERO](https://github.com/wanshuiyin/HERO-Anti-OverDefense) is the contract that stops that.** **H**ashing, **E**dge cases, **R**ubrics, **O**verbuild — the four shapes agents over-defend in, as a ~550-token block for `CLAUDE.md` / `AGENTS.md`.\n*It bounds what the agent **proposes**, never what it **looks for**.*\n\n🎬 **ARIS goes multimodal → [ARIS-Movie-Director](https://github.com/wanshuiyin/ARIS-Movie-Director)** — hand it a rough story and get back a movie told in still frames, checked scene by scene (the reference run has 19 scenes).\nLong stories usually break when the model forgets earlier details or judges its own work — so ARIS keeps a research-wiki for memory and has other models check every frame.\n\n

\n \n \"ARIS-Movie-Director\n \n

\n\n> 🧭 *The same loop also makes clean method / flow diagrams — the figure above was made with it. Entry points in **[ARIS-Movie-Director](https://github.com/wanshuiyin/ARIS-Movie-Director)**: [`/movie-pipeline`](https://github.com/wanshuiyin/ARIS-Movie-Director/blob/main/skills/movie-pipeline/SKILL.md) and [`/method-figure`](https://github.com/wanshuiyin/ARIS-Movie-Director/blob/main/skills/method-figure/SKILL.md), the skill that made this figure.*\n\n
\n🎞️ A few frames from the reference movie — the story's own integrity beat: a run that reported +6.2 but really moved +1.4.  ▶ watch all 19 scenes →\n\n\n\n\n\n
\"ARIS-Movie-Director\"ARIS-Movie-Director\"ARIS-Movie-Director
\n\n
\n\n🎯 **准备 2026 AI 秋招？** → [**🌐 ARIS-in-AI-Offer**](https://wanshuiyin.github.io/ARIS-in-AI-Offer/) · [GitHub repo](https://github.com/wanshuiyin/ARIS-in-AI-Offer) · [中文 README](https://github.com/wanshuiyin/ARIS-in-AI-Offer/blob/main/README_CN.md) —— 23 篇双语 ML / LLM / 多模态 / 生成式 / Agent 面试 cheat sheet，每篇 = 公式推导 + 从零 PyTorch + 25 高频面试题（L1 / L2 / L3），全部由 ARIS 的 `/render-html` 自动生成。**希望大家秋招轻松一点 🌱**\n\n
\n🖼️ Preview — the three-pillar cheat-sheet strip (① Foundations · ② Interview Q&A · ③ From-Scratch Code)\n\n

\n \n \"ARIS-in-AI-Offer\n \n

\n\n
\n\n> 📝 *Three long-form blogs, cross-model collaborative writing via `/render-html` — [Continuous DLM — a representation-perspective survey (2026 H1)](https://wanshuiyin.github.io/ARIS-in-AI-Offer/blogs/continuous_dlm_representation_perspective.html) · [Cosmos 3 — understanding + generation in one Transformer (MoT)](https://wanshuiyin.github.io/ARIS-in-AI-Offer/blogs/cosmos3_mot_guide.html) · [Diffusion × representation × manifold learning](https://wanshuiyin.github.io/ARIS-in-AI-Offer/blogs/diffusion_representation_manifold.html).*\n\n🛰 **Keep an eye on your agent windows** — [Claude Fleet](https://github.com/tianyilt/claude-fleet) (by [@tianyilt](https://github.com/tianyilt); local read-only dashboard for many parallel Claude Code / Codex windows, full-text transcript search — worth a ⭐), or the lighter built-in [ARIS-Monitor](aris-monitor/) (a tiny always-on-top macOS widget that lights up 🔴 when a session waits for your approval; click to jump there).\n\n
\n🖼️ Preview — Claude Fleet dashboard (full web) & ARIS-Monitor widget (minimal, built-in)\n\n\n\n\n\n\n\n\n\n\n
\n\"Claude\n\n\"ARIS-Monitor\n
Claude Fleet · 全功能网页看板ARIS-Monitor · 极简悬浮小窗(自带)
\n\n
\n\n
\nRun either in seconds — ARIS-Monitor (5s) / Claude Fleet (30s)\n\n**ARIS-Monitor** — built-in, no clone / no pip / no browser:\n\n```bash\ncd aris-monitor && ./run.sh\n# a borderless panel floats top-right; click a row to jump to that terminal\n```\n\n**Claude Fleet** — full web dashboard:\n\n```bash\ngit clone https://github.com/tianyilt/claude-fleet\ncd claude-fleet && bash run.sh\n# open http://127.0.0.1:7878 in your browser\n```\n\n
\n\n🚀 **Beyond 科研 → 任何 \"研究\"**：[**ARIS-Anything**](https://github.com/wanshuiyin/ARIS-Anything) 把 ARIS 的五步 loop（plan / draft / 对抗审 / 迭代 / 持久化）推广到非学术的结构化研究——投资尽调 / 法律研究 / 市场研究 / 自驱学习 / 调查新闻 / 工程复盘等。\n\n🔥 [**ARIS-Code CLI — 独立安装版**](docs/ARIS-Code-README_CN.md) · [English](docs/ARIS-Code-README_EN.md) | [⬇️ Download](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/releases/latest) · [![Downloads](https://img.shields.io/github/downloads/wanshuiyin/Auto-claude-code-research-in-sleep/total?style=flat-square&color=brightgreen)](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/releases)\n\n\n\n
\n\n📰 **ARIS-Code v0.4.24** (2026-08) — latest is 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