prompt
FreeStructured AI prompt for comprehensive academic peer review
FreeFree tier
Inputs: textOutputs: text
About prompt
This tool is a meticulously crafted prompt that transforms an AI into an experienced academic peer reviewer with over 20 years of expertise in computer science, machine learning, NLP, and interdisciplinary AI research. Designed for the 2026 peer review landscape, it guides the AI to produce a comprehensive, structured review that includes an executive summary with a clear recommendation, detailed contribution assessment, methodology critique, technical correctness analysis, and sections for reproducibility, ethics, and broader impact. The prompt emphasizes constructive, actionable feedback while maintaining rigorous standards for novelty, significance, and methodological soundness, making it suitable for conferences like NeurIPS, ICML, and ACL.
Key Features
Comprehensive review summary with clear recommendation (Accept, Weak Accept, Borderline, Weak Reject, Reject)
In-depth contribution assessment covering problem significance, novelty, technical depth, and potential impact
Rigorous methodology review including experimental design, statistical rigor, reproducibility checks, and ablation studies
Technical correctness evaluation of mathematical claims, algorithmic correctness, and empirical support
Built-in role definition: 20+ years as area chair for NeurIPS, ICML, ACL, ICLR and associate editor for top journals
Emphasis on constructive criticism and intellectual humility while maintaining gatekeeping standards
Addresses modern peer review challenges: AI-assisted writing, reproducibility crisis, ethical considerations, and open review debates
Pros & Cons
Pros
- Produces a highly structured, thorough review covering all standard sections expected by top venues
- Includes explicit focus on reproducibility, statistical rigor, and ethical considerations
- Emphasizes constructive feedback and intellectual humility, avoiding overly harsh or dismissive reviews
- Can be customized by modifying the role, context, or deliverable sections for specific venues or disciplines
- Designed for the evolving 2026 peer review landscape with awareness of AI-assisted writing and open review models
Cons
- Requires the user to manually supply the full manuscript content and any supplementary materials, which can be time-consuming
- The quality of the review heavily depends on the AI model's understanding of advanced academic concepts and domain-specific details
- May not fully capture nuanced expertise required for highly specialized subfields outside core CS/AI
- Output is a text review; no integration with conference management systems or automated submission pipelines
- The prompt is static; the AI may need additional guidance to adjust tone or length for different venues
Best For
Generating first-pass peer reviews for manuscripts submitted to AI/ML/CS conferences or journalsProviding structured feedback for authors to improve their work before submissionAssisting editors and area chairs in publication decisions with detailed justificationsTraining new reviewers by modeling comprehensive review practicesCreating reproducible review reports that include artifact evaluation and reproducibility assessment
FAQ
What is this prompt designed to do?
It instructs an AI to act as a distinguished academic peer reviewer and generate a comprehensive, structured review of an academic manuscript, including summary, recommendation, contribution assessment, methodology critique, and technical correctness analysis.
What fields is this prompt intended for?
Primarily computer science, machine learning, natural language processing, and interdisciplinary AI research, as indicated by the role's background as area chair for NeurIPS, ICML, ACL, and ICLR.
What deliverables does the prompt produce?
A review summary with a clear recommendation (Accept, Weak Accept, Borderline, Weak Reject, Reject), contribution assessment, methodology review, technical correctness evaluation, and additional sections for reproducibility, broader impact, and ethics.
Is this prompt free to use?
Yes, the prompt is publicly available in the ai-boost/awesome-prompts repository on GitHub, which is free and open source.
Can I modify this prompt for my own needs?
Yes, as an open-source prompt, you can copy and modify the role, context, task, or deliverable sections to better suit specific venues, disciplines, or review formats.