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.
Always load this skill when:
Thoroughly read and understand the paper before forming any judgments.
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. |
Read the paper systematically:
List the paper's main claims explicitly:
Claim 1: [Specific claim about contribution or finding]
Evidence: [What evidence supports this claim in the paper]
Strength: [Strong / Moderate / Weak]
Claim 2: [...]
...
Use web search to understand the research landscape:
Search queries:
- "[paper topic] state of the art [current year]"
- "[key method name] comparison benchmark"
- "[authors] previous work [topic]"
- "[specific technique] limitations criticism"
- "survey [research area] recent advances"
Use web_fetch on key related papers or surveys to understand where this work fits.
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 |
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 |
For each strength or weakness, provide:
Produce the final review using the template below.
# 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 the paper's core contribution, approach, and main findings.
State your overall assessment upfront: what the paper does well, where it falls short,
and whether the contribution is sufficient for the claimed venue/impact level.]
## Summary of Contributions
1. [First claimed contribution — one sentence]
2. [Second claimed contribution — one sentence]
3. [Additional contributions if any]
## Strengths
### S1: [Concise strength title]
[Detailed explanation with specific references to sections, figures, or tables in the paper.
Explain WHY this is a strength and its significance.]
### S2: [Concise strength title]
[...]
### S3: [Concise strength title]
[...]
## Weaknesses
### W1: [Concise weakness title]
[Detailed explanation with specific references. Explain the impact of this weakness on
the paper's claims. Suggest how it could be addressed.]
### W2: [Concise weakness title]
[...]
### W3: [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 that would clarify a concern or ambiguity]
2. [Question about methodology choices or alternative approaches]
3. [Question about generalizability or practical applicability]
## Minor Issues
- [Typos, formatting issues, unclear figures, notation inconsistencies]
- [Missing references that should be cited]
- [Suggestions for improved clarity]
## Literature Positioning
[How does this work relate to the current state of the art?
Are key related works cited? Are comparisons fair and comprehensive?
What important related work is missing?]
## Recommendations
**Overall Assessment**: [Accept / Weak Accept / Borderline / Weak Reject / Reject]
**Confidence**: [High / Medium / Low] — [Justification for confidence level]
**Contribution Level**: [Landmark / Significant / Moderate / Marginal / Below threshold]
### Actionable Suggestions for Improvement
1. [Specific, constructive suggestion]
2. [Specific, constructive suggestion]
3. [Specific, constructive suggestion]
| 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 |
Before finalizing the review, verify:
/mnt/user-data/outputs/review-{paper-topic}.md when working in sandboxpresent_files tooldeep-research skill — load both when the user wants the paper reviewed in the context of the broader field