A rigorous, critical reviewing style guide for academic paper review
⚡ Core Philosophy
Be critical, not charitable. Look for real problems, not surface-level compliments.
A comprehensive skill guide for conducting rigorous academic paper reviews with structured methodology and critical assessment frameworks.
| Feature | Description |
|---|---|
| 📝 Structured Template | Consistent review format with clear sections |
| 🎯 4D Assessment | Soundness · Presentation · Significance · Originality |
| 🚩 Red Flag Checklists | Identify common issues systematically |
| ✅ Baseline Completeness | Essential comparison requirements |
| 🔍 Prior Work Verification | Check arXiv and preprint servers |
# Clone the repository
git clone https://github.com/Dominic789654/critical-reviewer-skill.git
# Read the complete guide
cat SKILL.md| Rating | Meaning | Description |
|---|---|---|
| ⭐⭐⭐⭐ | 4 (Excellent) | Rare, with almost no flaws |
| ⭐⭐⭐ | 3 (Good) | Minor issues, overall well-executed |
| ⭐⭐ | 2 (Fair) | Major defects but core idea salvageable |
| ⭐ | 1 (Poor) | Fundamental flaws |
.
├── 📘 SKILL.md # Core reviewing guide
├── 📗 docs/guide.md # Detailed usage guide
├── 🌐 index.md # Website homepage
└── 🎨 assets/ # Logo and images
When reviewing a paper, copy the template from SKILL.md and follow the structured approach:
- Summary - Objective overview without judgment
- Strengths - Genuine contributions (not praise)
- Weaknesses - Specific, actionable issues
- Key Questions - Clarifications for authors
- Ratings - 4D assessment scores
- Path to Acceptance - Concrete improvement steps
Contributions are welcome! Please feel free to:
This guide is for methodology education only:
- ✅ Use for learning review techniques
- ✅ Reference for improving your own reviews
- ❌ Never share real confidential peer review content
- ❌ Do not post reviews from actual conferences
Real peer review content is confidential and protected by conference ethics policies.
This project is licensed under the MIT License - see the LICENSE file for details.
- Inspired by best practices from major ML conference reviewing
- Structured methodology based on ICLR/NeurIPS/ICML review guidelines
Made with ❤️ for better academic peer review