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

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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")