academic-paper-review
Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive fee
By bytedance · 2,261 installs
npx skills add bytedance/deer-flow --skill academic-paper-review
Source repository · Upstream listing
Academic Paper Review Skill
Overview
This skill produces structured, peer review quality analyses of academic papers and research publications. It follows established academic review standards used by top tier venues (NeurIPS, ICML, ACL, Nature, IEEE) to provide rigorous, constructive, and balanced assessments.
The review covers summary, strengths, weaknesses, methodology assessment, contribution evaluation, literature positioning, and actionable recommendations — all grounded in evidence from the paper itself.
Core Capabilities
Parse and comprehend academic papers from uploaded PDFs or fetched URLs
Generate structured reviews following top venue review templates
Assess methodology rigor (experimental design, statistical validity, reproducibility)
Evaluate novelty and significance of contributions
Position the work within the broader research landscape via targeted literature search
Identify limitations, gaps, and potential improvements
Produce both detailed review and concise executive summary formats
Support papers in any scientific domain (CS, biology, physics, social sciences, etc.)
When to Use This Skill
Always load this skill when:
User provides a paper URL (arXiv, DOI, conference proceedings, journal link)
User uploads a PDF of a research paper or preprint
User asks to "review", "analyze", "critique", "assess", or "summarize" a research paper
User wants to understand the strengths and weaknesses of a study
User requests a peer review style evaluation of academic work
User asks for help preparing a review for a conference or journal submission
Review Methodology
Phase 1: Paper Comprehension
Thoroughly read and understand the paper before forming any judgments.
Step 1.1: Identify Paper Metadata
Extract and record:
Field Description
Title Full paper title
Authors Author list and affiliations
Venue / Status Publication venue, preprint server, or submission status
Year Publication or submission year
Domain Research field and subfield
Paper Type Empirical, theoretical, survey, position paper, systems paper, etc.
Step 1.2: Deep Reading Pass
Read the paper systematically:
1. Abstract & Introduction — Identify the claimed contributions and motivation
2. Related Work — Note how authors position their work relative to prior art
3. Methodology — Understand the proposed approach, model, or framework in detail
4. Experiments / Results — Examine datasets, baselines, metrics, and reported outcomes
5. Discussion & Limitations — Note any self identified limitations
6. Conclusion — Compare concluded claims against actual evidence presented
Step 1.3: Key Claims Extraction
List the paper's main claims explicitly:
Phase 2: Critical Analysis
Step 2.1: Literature Context Search
Use web search to understand the research landscape:
Use web fetch on key related papers or surveys to understand where this work fits.
Step 2.2: Methodology Assessment
Evaluate the methodology using the following framework:
Criterion Questions to Ask Rating
Soundness Is the approach technically correct? Are there logical flaws? 1 5
Novelty What is genuinely new vs. incremental improvement? 1 5
Reproducibility Are details sufficient to reproduce? Code/data available? 1 5
Experimental Design Are baselines fair? Are ablations adequate? Are datasets appropriate? 1 5
Statistical Rigor Are results statistically significant? Error bars reported? Multiple runs? 1 5
Scalability Does the approach scale? Are computational costs discussed? 1 5
Step 2.3: Contribution Significance Assessment
Evaluate the significance level:
Level Description Criteria
Landmark Fundamentally changes the field New paradigm, widely applicable breakthrough
Significant Strong contribution advancing the state of the art Clear improvement with solid evidence
Moderate Useful contribution with some limitations Incremental but valid improvement
Marginal Minimal advance over existing work Small gains, narrow applicability
Below threshold Does not meet publication standards Fundamental flaws, insufficient evidence
Step 2.4: Strengths and Weaknesses Analysis
For each strength or weakness, provide:
What : Specific observation
Where : Section/figure/table reference
Why it matters : Impact on the paper's claims or utility
Phase 3: Review Synthesis
Step 3.1: Assemble the Structured Review
Produce the final review using the template below.
Review Output Template
Review Principles
Constructive Criticism
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, and 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 after the problem formulation." (specific, actionable)
Ethical Review Practices
Do NOT dismiss work based on author reputation or affiliation
Evaluate the work on its own merits
Flag potential ethical concerns (bias in datasets, dual use implications) constructively
Maintain confidentiality of unpublished work
Adaptation by Paper Type
Paper Type Focus Areas
Empirical Experimental design, baselines, statistical significance, ablations, reproducibility
Theoretical Proof correctness, assumption reasonableness, tightness of bounds, connection to practice
Survey Comprehensiveness, taxonomy quality, coverage of recent work, synthesis insights
Systems Architecture decisions, scalability evidence, real world deployment, engineering contributions
Position Argument coherence, evidence for claims, impact potential, fairness of characterizations
Common Pitfalls to Avoid
❌ Reviewing the paper you wish was written instead of the paper that was 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
❌ Treating absence of comparison to your own work as a weakness
❌ Providing only a summary without critical analysis
Quality Checklist
Before finalizing the review, verify:
[ ] Paper was read completely (not just abstract and introduction)
[ ] All major claims are identified and evaluated against evidence
[ ] At least 3 strengths and 3 weaknesses are provided with specific references
[ ] The methodology assessment table is complete with ratings and justifications
[ ] Questions for authors target genuine ambiguities, not rhetorical critiques
[ ] Literature search was conducted to contextualize the contribution
[ ] Recommendations are actionable and constructive
[ ] The overall assessment is consistent with the identified strengths and weaknesses
[ ] The review tone is professional and respectful
[ ] Minor issues are separated from major concerns
Output Format
Output the complete review in Markdown format
Save the review to /mnt/user data/outputs/review {paper topic}.md when working in sandbox
Present the review to the user using the present files tool
Notes
This skill complements the deep research skill — load both when the user wants the paper reviewed in the context of the broader field
For papers behind paywalls, work with whatever content is accessible (abstract, publicly available versions, preprint mirrors)
Adapt the review depth to the user's needs: a brief assessment for quick triage versus a full review for submission preparation
When reviewing multiple papers comparatively, maintain consistent criteria across all reviews
Always disclose limitations of your review (e.g., "I could not verify the proofs in Appendix B in detail")