wanshuiyin/Auto-claude-code-research-in-sleep
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.
Overview
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.
Best for
- Evaluating Auto-claude-code-research-in-sleep for Python AI workflows.
- Comparing a GitHub project with 10,069 stars and current repository activity.
Pros
- Auto-claude-code-research-in-sleep has visible GitHub traction with 10,069 stars. Topics: ai-research, ai-tools, aris.
- The GitHub repository is the primary evaluation surface.
Cons
- Production fit still depends on documentation depth, issue activity, and release cadence.
- License review should confirm the MIT terms fit your use case.
Production readiness
Auto-claude-code-research-in-sleep should be validated with its README, release history, open issues, and integration requirements before production use.
License risk
MIT is reported by GitHub; review the repository license before redistribution or commercial use.
Install
git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git ~/aris_reponpm install -g @anthropic-ai/claude-codenpm install -g @openai/codexgit clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep.git