Agentic-Systems-Lab rigorous

A comprehensive suite of tools, built to liberate science by making the creation, evaluation, and dissemination of research more transparent, affordable, and efficient.

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popularity 41

growth 0

activity 15

freshness 100

community 33

Rigorous AI-Powered Scientific Manuscript Analysis

v0.2 Now Live: The latest version of the AI Reviewer (v0.2) is now available at https://www.rigorous.review/. Upload your manuscript, provide context on your target journal and receive structured feedback directly online via an interactive interface — now with progress tracking built in. Once initial testing of v0.2 is complete, we will make all module prompts open source to promote transparency and enable community contributions.

Help Us Improve! Please provide feedback via this short feedback form to help us improve the system.

Support AI Reviewer v0.3 by rocking some peer-reviewed merch 👕🧠 – grab yours here – GitHub contributors get free gear.

Vision

This repository is intended for tools that make the creation, evaluation, and distribution of scientific knowledge more transparent, cheaper, faster, and better. Let's build this future together!

Project Structure

Agent1_Peer_Review: Multiagent AI review system for comprehensive manuscript analysis, detailed feedback, and PDF report generation (v0.1).
Agent2_Outlet_Fit: (In Development) Tool for evaluating manuscript fit with target journals/conferences.

Current Status

Active Tools

Agent1_Peer_Review: ✅ v0.1 Ready for use!
- Comprehensive manuscript analysis with specialized agents
- Detailed feedback on sections, scientific rigor, and writing quality (including quality control loops)
- JSON output with actionable recommendations
- PDF report generation
- 📄 Detailed Documentation and Key Areas for Contribution

In Development

Agent2_Outlet_Fit: 🚧 In Development
- Core functionality being implemented
- Integration with Agent1_Peer_Review in progress
- Testing and validation ongoing
- 🛠️ Development Plan

Future Modules and Ideas

Embedding-based similarity analysis (by @andjar): Use embeddings (as in The landscape of biomedical research) to compare a paper’s abstract with existing literature. This could help surface uncited but relevant work and suggest suitable journals based on similarity clusters.
Support for Drafting Reviewer Reponses.
Feedback on Research Proposals and Protocols.
AI-enabled document creation tool ("Cursor for Papers").

Requirements

Python 3.7+
OpenAI API key (the system can be adapted to alternative LLMs, including locally hosted ones)
PDF manuscripts to analyze
Dependencies listed in each tool's requirements.txt

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Citation

If you use the Rigorous AI Reviewer in your research or project, please cite:

@software{rigorous_ai_reviewer2025,
  author = {Jakob, Robert and O'Sullivan, Kevin},
  title = {Rigorous AI Reviewer: Enabling AI for Scientific Manuscript Analysis},
  year = {2025},
  publisher = {GitHub},
  url = {https://github.com/robertjakob/rigorous}
}