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:
Step 1.2: Deep Reading Pass
Read the paper systematically:
- Abstract & Introduction — Identify the claimed contributions and motivation
- Related Work — Note how authors position their work relative to prior art
- Methodology — Understand the proposed approach, model, or framework in detail
- Experiments / Results — Examine datasets, baselines, metrics, and reported outcomes
- Discussion & Limitations — Note any self-identified limitations
- 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:
Step 2.3: Contribution Significance Assessment
Evaluate the significance level:
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
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}.mdwhen working in sandbox - Present the review to the user using the
present_filestool
Notes
- This skill complements the
deep-researchskill — 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")

