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.
ARIS (Auto-Research-In-Sleep) is a Markdown-only, framework-free methodology for automating machine learning research workflows, distributed as a set of skill files that run inside Claude Code, Codex CLI, Cursor, and other LLM agent runtimes without requiring any proprietary platform. Its core loop assigns three roles to the agent: a breadth pass for idea discovery and literature scanning, a cross-model adversarial review step where multiple models critique drafts, and a research wiki that persists findings as structured memory across sessions. Concrete slash-commands include `/render-html` for generating fact-checked HTML write-ups, `/paper-talk` for producing presentation slides, and `/homepage-generator` for building academic homepages from CV data. The project also ships ARIS-Monitor, a dependency-free Python floating window that flags which Claude Code sessions are waiting for user authorization. Researchers and ML practitioners who want unattended overnight experiment tracking, automated paper drafting, and cross-model peer review without adopting a heavyweight framework are the primary audience.
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Healthy fork ratio
- ✓Clear description
- ✓Topics declared
- ✓Documented (README)
git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleepAwesome Lists overview
# 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>
[](https://huggingface.co/papers/2605.03042) · [](https://wanshuiyin.github.io/Auto-claude-code-research-in-sleep/ARIS_INTRO.html) · [](docs/aris_intro_slides.pdf) · [](AGENT_GUIDE.md) · [](https://mp.weixin.qq.com/s/tDniVryVGjDkkkWl-5sTkQ) · [](https://github.com/VoltAgent/awesome-agent-skills) · [-orange?style=flat)](https://aidigitalcrew.com) · [](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/stargazers) · [💬 Join Community](#community) · [](#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 **[ARIS-Code](docs/ARIS-Code-README_EN.md)** CLI — enjoy any way you like!*
🌱 *ARIS is a methodology, not a platform. What matters is the research workflow — take it wherever you go.*
🤖 **AI agents:** Read [`AGENT_GUIDE.md`](AGENT_GUIDE.md) instead — structured for LLM consumption, not human browsing.
🛡️ **ARIS audits its own output → now [Anti-Autoresearch](https://github.com/wanshuiyin/Anti-Autoresearch) audits everyone's.** It catalogs **46 integrity hack-patterns across 8 families (A–H), plus 13 zero-verdict-weight AI-style impressions and 2 advisory signals — 61 signals total** — and checks a submission for them **end-to-end**, producing a deterministic, reviewer-ready integrity report. *Self-consistency + fabrication forensics, **not** an AI-text detector.*
<p align="center"><em>The field has put up with unreliable autoresearch long enough —<br>Anti-Autoresearch is the read that finally catches it.</em></p>
🎬 **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).
Long 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.
<p align="center">
<a href="https://github.com/wanshuiyin/ARIS-Movie-Director">
<img src="docs/aris-movie-director-method.png" alt="ARIS-Movie-Director method — the audited spiral: authored source of truth (asset library · outline · storyboard · comic.json) → per-panel image_gen + cross-model panel_gate (blind token-diff, single-vote veto) → research-wiki audit trace → assembly + release" width="100%">
</a>
</p>
> 🧭 *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.*
<details>
<summary>🎞️ <i>A few frames from the reference movie — the story's own integrity beat: a run that <b>reported <code>+6.2</code></b> but <b>really moved <code>+1.4</code></b>.</i> <b><a href="https://wanshuiyin.github.io/ARIS-Movie-Director/comic/">▶ watch all 19 scenes →</a></b></summary>
<table><tr>
<td width="33%"><a href="https://wanshuiyin.github.io/ARIS-Movie-Director/comic/"><img src="https://raw.githubusercontent.com/wanshuiyin/ARIS-Movie-Director/main/docs/preview_audit.webp" alt="ARIS-Movie-Director frame — the evaluator-integrity audit page" width="100%"></a></td>
<td width="33%"><a href="https://wanshuiyin.github.io/ARIS-Movie-Director/comic/"><img src="https://raw.githubusercontent.com/wanshuiyin/ARIS-Movie-Director/main/docs/preview_panels.webp" alt="ARIS-Movie-Director frame — a multi-panel scene" width="100%"></a></td>
<td width="33%"><a href="https://wanshuiyin.github.io/ARIS-Movie-Director/comic/"><img src="https://raw.githubusercontent.com/wanshuiyin/ARIS-Movie-Director/main/docs/preview_fix.webp" alt="ARIS-Movie-Director frame — the integrity beat (reported +6.2, really moved +1.4)" width="100%"></a></td>
</tr></table>
</details>
🎯 **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 🌱**
<details>
<summary><b>🖼️ Preview</b> — the three-pillar cheat-sheet strip (① Foundations · ② Interview Q&A · ③ From-Scratch Code)</summary>
<p align="center">
<a href="https://github.com/wanshuiyin/ARIS-in-AI-Offer">
<img src="https://raw.githubusercontent.com/wanshuiyin/ARIS-in-AI-Offer/main/assets/preview_strip.jpg" alt="ARIS-in-AI-Offer preview — ① Foundations + ② Interview Q&A + ③ From-Scratch Code, three columns from a representative cheat sheet" width="100%">
</a>
</p>
</details>
> 📝 *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).*
🛰 **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).
<details>
<summary><b>🖼️ Preview</b> — Claude Fleet dashboard (full web) & ARIS-Monitor widget (minimal, built-in)</summary>
<table align="center" width="100%">
<tr>
<td width="66%" align="center" valign="top">
<a href="https://github.com/tianyilt/claude-fleet"><img src="assets/claude-fleet-preview.png" width="100%" alt="Claude Fleet — full local web dashboard for many concurrent Claude Code / Codex windows (triage, Focus, full-text search, skill/memory analytics)"></a>
</td>
<td width="34%" align="center" valign="top">
<a href="aris-monitor/"><img src="aris-monitor/assets/screenshot.png" width="100%" alt="ARIS-Monitor — minimal always-on-top floating widget showing which Claude Code sessions need approval (calm all-clear vs red ATTENTION)"></a>
</td>
</tr>
<tr>
<td align="center"><b><a href="https://github.com/tianyilt/claude-fleet">Claude Fleet</a></b> · 全功能网页看板</td>
<td align="center"><b><a href="aris-monitor/">ARIS-Monitor</a></b> · 极简悬浮小窗(自带)</td>
</tr>
</table>
</details>
<details>
<summary><b>Run either in seconds</b> — ARIS-Monitor (5s) / Claude Fleet (30s)</summary>
**ARIS-Monitor** — built-in, no clone / no pip / no browser:
```bash
cd aris-monitor && ./run.sh
# a borderless panel floats top-right; click a row to jump to that terminal
```
**Claude Fleet** — full web dashboard:
```bash
git clone https://github.com/tianyilt/claude-fleet
cd claude-fleet && bash run.sh
# open http://127.0.0.1:7878 in your browser
```
</details>
🚀 **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。
🔥 [**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) · [](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/releases)
<table>
<tr>
<td valign="top" width="60%">
📰 **ARIS-Code v0.4.22** (2026-07) — latest is the **skills-resync + GPT-5.6-Sol release**: the bundled skill set catches up 93 commits to this repo (**79 bundled skills** — incl. the new `paper-poster-html` measurement-gated poster pipeline and `meta-apply` — plus 11 new shared-references docs), the revWhat people ask about Auto-claude-code-research-in-sleep
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+
wanshuiyin/Auto-claude-code-research-in-sleep is awesome lists for the Claude AI ecosystem. 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. It has 13.9k GitHub stars and was last updated 5d ago.
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+
You can install Auto-claude-code-research-in-sleep by cloning the repository (https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
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wanshuiyin/Auto-claude-code-research-in-sleep is maintained by wanshuiyin. The last recorded GitHub activity is from 5d ago, with 62 open issues.
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