Fully Autonomous AI Research System with Self-Evolution, built natively on Claude Code
# Add to your Claude Code skills
git clone https://github.com/Sibyl-Research-Team/AutoResearch-SibylSystemInspired by the pioneering work of The AI Scientist, FARS, and AutoResearch, Sibyl takes the vision further by building natively on Claude Code to fully leverage its agent ecosystem — skills, plugins, MCP servers, and multi-agent teams.
Sibyl is a fully autonomous AI scientist that drives end-to-end ML research — from literature survey and hypothesis generation to GPU experiment execution and conference-ready paper writing. It operates as an autonomous research organization: 20+ specialized AI agents debate ideas, design and run GPU experiments, write papers, and critically review their own work — all without human intervention.
Key capabilities: automated literature review, multi-agent idea debate, experiment planning & GPU-parallel execution, multi-agent paper writing & peer review, autonomous iteration with quality gates, and cross-project self-evolution. Supports NeurIPS/ICML/ICLR-level output with LaTeX compilation.
No comments yet. Be the first to share your thoughts!
What truly sets Sibyl apart is its dual-loop architecture: