ARIS: Autonomous ML Research Tool for Efficient Workflows

ARIS (Auto-Research-In-Sleep) is a lightweight tool designed for autonomous machine learning research. It facilitates cross-model review loops, idea discovery, and experiment automation using a Markdown-only approach. This tool operates without dependencies, allowing users to engage in research workflows seamlessly.

Key features:

• Zero dependencies - Operates entirely on plain Markdown files.
• Flexible integration - Compatible with various LLM agents like Claude Code, Codex, and OpenClaw.
• Research Wiki - A persistent knowledge base for managing papers, ideas, and experiments.
• Multi-file memory index - Enhances the organization of research data.
• Auto-retry mechanism - Automatically handles network errors during research execution.

ARIS is particularly useful for researchers looking to streamline their workflows and enhance collaboration across different AI models.