ARIS (Auto-Research-In-Sleep)

github.com/wanshuiyin/auto-claude-code-research-in-sleep
Active14.7Kupdated 2 weeks ago
Python
MIT

Lightweight Markdown-only skills for autonomous ML research with cross-model review loops, idea discovery, and experiment automation; no framework lock-in, works with Claude Code, Codex, OpenClaw, or any LLM agent (12.8K+ stars, MIT License, 2026)

Sourced from

  • Awesome AI for Sciencegithub.com/wanshuiyin/auto-claude-code-research-in-sleep
  • GitHubgithub.com/wanshuiyin/auto-claude-code-research-in-sleep

Related resources

Comprehensive Claude Code skill suite covering the full academic pipeline from deep research and paper writing to multi-perspective peer review, revision, and finalization; features multi-agent teams, PRISMA systematic review, style calibration, claim-level citation audits, integrity gates, and human-in-the-loop safeguards (38K+ stars, CC BY-NC 4.0, 2026)

Active38.4K1 month ago
Python
NOASSERTION

Robust, lightweight infrastructure for multi-agent autonomous self-evolution, built for autoresearch; agents run in isolated git worktrees, share knowledge through a common state directory, and are scored by a grader daemon; natively integrated with Claude Code, Codex, Cursor Agent, OpenCode, and Kiro (672+ stars, Apache 2.0)

Active8321 month ago
Python
Apache-2.0

AI coding assistant for JupyterLab with agent mode, supporting arbitrary LLM providers (2025+)

Active3253 weeks ago
Python
GPL-3.0

Semi-automated research assistant for academic research and software development, supporting Claude Code, Codex CLI, Kimi Code CLI, and OpenCode across ideation, coding, experiments, writing, and publication (Galaxy-Dawn, 4.5K+ stars, MIT License, 2026)

Active4.6K1 month ago
Python
MIT

Offline-first scientific writing workspace powered by Claude, integrating LaTeX, Python, and 100+ scientific skills with local execution, Zotero integration, and privacy-focused design (2026)

Active1.8K4 weeks ago
TypeScript
MIT

End-to-end autonomous AI research engine that turns an idea into a complete LaTeX paper by dispatching real computational experiments to local GPUs or SLURM clusters, collecting actual results, generating figures/tables, and writing a data-grounded manuscript rather than LLM hallucinations (OpenRaiser, 1.5K+ stars, MIT License, 2026)

Active1.4K3 months ago
Python
MIT