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.
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!
- 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.
- 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
- Agent2_Outlet_Fit: 🚧 In Development
- Core functionality being implemented
- Integration with Agent1_Peer_Review in progress
- Testing and validation ongoing
- 🛠️ Development Plan
- 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").
- 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
Contributions are welcome! Please feel free to submit a Pull Request.
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}
}
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