AliManjotho

AliManjotho / open-reviewer

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OpenReviewer is an automated multi-agent system for deep, evidence-driven research paper review, validation, and integrity auditing across methodology, experiments, citations, and cross-section consistency.

18
8
69% credibility
Found Mar 31, 2026 at 18 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

OpenReviewer is a system that processes research paper PDFs to create automated review reports highlighting strengths, weaknesses, issues, and recommendations.

How It Works

1
🔍 Discover OpenReviewer

You learn about OpenReviewer, a helpful assistant that checks research papers like a team of expert reviewers before submission.

2
📥 Set it up

You follow easy pictures and steps to get the tool ready on your computer.

3
📄 Drop in your paper

You place the PDF of your research paper into the ready folder.

4
🚀 Ask for a review

You simply tell the tool to review your paper, and it gets to work examining every part.

5
Pick your review way
📄
One Paper

Get full feedback on a single paper.

📚
Many Papers

Review a whole set of papers together.

🕵️
Integrity Audit

Spot tricks, bad data, or fake claims.

⚖️
Compare Versions

Rank different drafts to pick the best.

6
📊 Get your report

You receive a friendly report with scores, good points, problems, fixes, and advice.

✅ Stronger paper ready

Your paper shines brighter, full of fixes, and set to wow real reviewers.

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Star Growth

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AI-Generated Review

What is open-reviewer?

OpenReviewer automates deep, evidence-driven reviews of research papers, auditing methodology, experiments, citations, and cross-section consistency using a TypeScript-based multi-agent system. Drop PDF papers into a folder and run CLI commands like /review-paper, /batch-review, /audit-paper, or /compare-papers via OpenCode to get structured outputs: JSON reviews, Markdown reports, HTML scorecards with issues, strengths, weaknesses, and recommendations. It solves pre-submission blind spots by flagging integrity issues before journals like ICLR see them.

Why is it gaining traction?

This openreview github project stands out as an open source reviewer for automated, multi-agent auditing across citations and experiments, unlike basic linters or manual open reviewers. Developers hook into its evidence-driven pipelines for batch processing and paper comparisons, delivering traceable scorecards that mimic ICLR reviewer open workflows. The CLI simplicity and outputs in multiple formats make it a quick win for scaling open reviewer jurnal tasks.

Who should use this?

Academic researchers polishing papers for submission, journal editors running open recruitment reviewer jurnal checks, or conference organizers auditing batches for consistency. Ideal for PhD students validating experiments and citations pre-deadline, or open ai pr reviewer teams spotting fraud in submissions.

Verdict

Promising skeleton for an open ai code reviewer-style tool, but at 18 stars and 0.7% credibility score, it's immature—parsers and analysis are placeholders needing real AI integrations. Try for prototyping automated auditing, but expect to extend heavily for production.

(187 words)

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