Academic Paper Review
SkillDev toolsStructured peer-review of academic papers.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Academic Paper Review skill
What this skill tells your AI
The instructions your AI receives, as published by hezaohezao/poirot in poirot/backend/agents/skill/builtin_skills/research/academic-paper-review/SKILL.md and read by ahel’s review.
Overview
Produces structured, peer-review-quality analyses of academic papers. Follows review standards used by top-tier venues (NeurIPS, ICML, ACL, Nature, IEEE) to provide rigorous, constructive, and balanced assessments.
Covers summary, strengths, weaknesses, methodology assessment, contribution evaluation, literature positioning, and actionable recommendations — all grounded in evidence from the paper itself.
When to Use
- User provides a paper URL (arXiv, DOI, conference proceedings)
- User asks to "review", "analyze", "critique", "assess", or "summarize" a research paper
- User wants to understand strengths and weaknesses of a study
- User requests a peer-review-style evaluation
Review Methodology
Phase 1: Paper Comprehension
Step 1.1: Identify Paper Metadata
Extract: Title, Authors, Venue/Status, Year, Domain, Paper Type (Empirical / Theoretical / Survey / Systems / Position).
Step 1.2: Deep Reading Pass
Read the paper systematically using browse_page:
- Abstract & Introduction — Identify claimed contributions and motivation
- Related Work — Note how authors position relative to prior art
- Methodology — Understand the proposed approach in detail
- Experiments / Results — Examine datasets, baselines, metrics, outcomes
- Discussion & Limitations — Note self-identified limitations
- Conclusion — Compare concluded claims against actual evidence
Step 1.3: Key Claims Extraction
List the paper's main claims explicitly:
Claim 1: [Specific claim]
Evidence: [What evidence supports this]
Strength: [Strong / Moderate / Weak]
Phase 2: Critical Analysis
Step 2.1: Literature Context Search
Use web_search to understand the research landscape:
"[paper topic] state of the art [current year]"
"[key method name] comparison benchmark"
"[specific technique] limitations criticism"
Use browse_page on key related papers or surveys.
Step 2.2: Methodology Assessment
| Criterion | Questions to Ask | Rating |
|---|---|---|
| Soundness | Is the approach technically correct? | 1-5 |
| Novelty | What is genuinely new vs incremental? | 1-5 |
| Reproducibility | Are details sufficient? Code/data available? | 1-5 |
| Experimental Design | Are baselines fair? Ablations adequate? | 1-5 |
| Statistical Rigor | Results significant? Error bars? Multiple runs? | 1-5 |
| Scalability | Does it scale? Computational costs discussed? | 1-5 |
Step 2.3: Contribution Significance
| Level | Description |
|---|---|
| Landmark | Fundamentally changes the field |
| Significant | Strong contribution advancing state of the art |
| Moderate | Useful contribution with some limitations |
| Marginal | Minimal advance over existing work |
| Below threshold | Does not meet publication standards |
Phase 3: Review Synthesis
Produce the final review using this template:
# Paper Review: [Paper Title]
## Paper Metadata
- **Authors**: [Author list]
- **Venue**: [Publication venue or preprint server]
- **Year**: [Year]
- **Domain**: [Research field]
- **Paper Type**: [Empirical / Theoretical / Survey / Systems / Position]
## Executive Summary
[2-3 paragraph summary of core contribution, approach, and main findings.
State overall assessment upfront.]
## Summary of Contributions
1. [First claimed contribution]
2. [Second claimed contribution]
## Strengths
### S1: [Concise strength title]
[Detailed explanation with specific references to sections, figures, tables.]
### S2: [Concise strength title]
[...]
## Weaknesses
### W1: [Concise weakness title]
[Detailed explanation. Explain impact. Suggest how to address.]
### W2: [Concise weakness title]
[...]
## Methodology Assessment
| Criterion | Rating (1-5) | Assessment |
|-----------|:---:|------------|
| Soundness | X | [Brief justification] |
| Novelty | X | [Brief justification] |
| Reproducibility | X | [Brief justification] |
| Experimental Design | X | [Brief justification] |
| Statistical Rigor | X | [Brief justification] |
| Scalability | X | [Brief justification] |
## Questions for the Authors
1. [Specific question]
2. [Question about methodology choices]
## Literature Positioning
[How does this work relate to current state of the art? Key related works cited?]
## Recommendations
**Overall Assessment**: [Accept / Weak Accept / Borderline / Weak Reject / Reject]
**Confidence**: [High / Medium / Low]
**Contribution Level**: [Landmark / Significant / Moderate / Marginal / Below threshold]
### Actionable Suggestions for Improvement
1. [Specific, constructive suggestion]
2. [Specific, constructive suggestion]
Review Principles
- Always suggest how to fix it — Don't just point out problems; propose solutions
- Give credit where due — Acknowledge genuine contributions even in flawed papers
- Be specific — Reference exact sections, equations, figures, tables
- Separate minor from major — Distinguish fatal flaws from fixable issues
Objectivity Standards
- ❌ "This paper is poorly written" (vague, unhelpful)
- ✅ "Section 3.2 introduces notation X without formal definition, making the proof in Theorem 1 difficult to follow. Consider adding a notation table." (specific, actionable)
Adaptation by Paper Type
| Paper Type | Focus Areas |
|---|---|
| Empirical | Experimental design, baselines, statistical significance, ablations |
| Theoretical | Proof correctness, assumption reasonableness, tightness of bounds |
| Survey | Comprehensiveness, taxonomy quality, coverage of recent work |
| Systems | Architecture decisions, scalability evidence, real-world deployment |
| Position | Argument coherence, evidence for claims, impact potential |
Common Pitfalls
- ❌ Reviewing the paper you wish was written instead of the paper submitted
- ❌ Demanding additional experiments that are unreasonable in scope
- ❌ Penalizing the paper for not solving a different problem
- ❌ Being overly influenced by writing quality versus technical contribution
- ❌ Providing only a summary without critical analysis
Quality Checklist
- Paper read completely (not just abstract and introduction)
- All major claims identified and evaluated against evidence
- At least 3 strengths and 3 weaknesses with specific references
- Methodology assessment table complete with ratings and justifications
- Literature search conducted to contextualize the contribution
- Recommendations are actionable and constructive
- Review tone is professional and respectful
Output
- Output the complete review in Markdown
- Save to
.poirot/outputs/review-{paper-topic}.mdviawrite_file - Present to user via
present_files
Signals
- GitHub stars
- 220
- Forks
- 19
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
academic-paper-review- Source
- github.com/hezaohezao/poirot