Summary

This repository addresses the need for AI-assisted scientific research by collaboratively curating agents, skills, workflows, tools, and best practices across the full research lifecycle. Aimed at researchers and engineers, it provides a structured knowledge base for discovering and adopting AI capabilities to accelerate discovery and improve reproducibility.

How It Works

The project organizes AI research components into nine distinct scientific lifecycle stages, from ideation to dissemination. It emphasizes collecting reusable, verifiable, and evolving AI capabilities. This community-driven curation distills effective AI tools and workflows, fostering shared understanding and accelerating adoption.

Quick Start & Requirements

This repository is a curated index, not a single installable package. Users must follow links to individual projects for their specific installation instructions, dependencies (e.g., Python, hardware), and setup guides. Links to official quick-start guides and demos are provided for many listed projects.

Highlighted Details

• Comprehensive mapping of AI research components across nine lifecycle stages: Full-process, Direction Scanning, Literature Research, Method Design, Experiment Execution, Visualization, Paper Writing, Reproducibility, and Dissemination.
• Features high-impact projects like autoresearch (88.6k stars), nature-skills (23.3k stars), STORM (29.4k stars), and AI-Scientist (14.1k stars).
• Strong emphasis on reproducibility, verifiability, and community-driven best practices for AI in science.
• Includes a "Best Practices" section with practical tutorials.

Maintenance & Community

Designed for open, collaborative building, originating from the "Researching with Agents" salon series. Contributions are encouraged by adding new projects or best practices directly to tables. Leverages platforms like ModelScope for demos and community engagement.

Licensing & Compatibility

The "Awesome-Vibe-Research" repository itself lacks an explicit license. It curates numerous open-source projects; users must consult individual project licenses for compatibility and commercial use restrictions.

Limitations & Caveats

As a curated list, users must independently evaluate and integrate individual components. Tool effectiveness depends on specific implementations and research context. The "Stars" count is auto-updated via GitHub Actions, but initial project additions require manual formatting.