ClaudeSuperPower

Auto-claude-code-research-in-sleep

Skill

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.

Install

git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git ~/.claude/skills/auto-claude-code-research-in-sleep

What is Auto-claude-code-research-in-sleep?

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.

Trust

94/100 · Excellent

1 factor scored below maximum

Documentation

README · ~100 min read

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

Hugging Face Daily Paper · #1 Paper of the Day

Technical Report · ARIS Intro (HTML) · ARIS Intro Slides — VALSE 2026 · AI Agents · Featured on PaperWeekly · Featured in awesome-agent-skills · AI Digital Crew - Project of the Day · GitHub stars · 💬 Join Community · Cite

💡 Use ARIS as a skill-based workflow in Claude Code / Codex CLI / Cursor / Trae / Antigravity / GitHub Copilot CLI / OpenClaw, or get the full experience with the standalone ARIS-Code 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 instead — structured for LLM consumption, not human browsing.

🛡️ ARIS audits its own output → now 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.

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

🎬 ARIS goes multimodal → 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.

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

🧭 The same loop also makes clean method / flow diagrams — the figure above was made with it. Entry points in ARIS-Movie-Director: /movie-pipeline and /method-figure, the skill that made this figure.

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