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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,
$ npx -y skills add bytedance/deer-flow --skill academic-paper-review --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/academic-paper-reviewContext preview
The summary Claude sees to decide when to auto-load this skill.
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,
name: academic-paper-review description: 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 feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
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:
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
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**: [R
On February 28th, 2026, DeerFlow claimed the 🏆 #1 spot on GitHub Trending following the launch of version 2. Thanks a million to our incredible community — you made this happen!
Repo: bytedance/deer-flow
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