Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/HezaoHezao/poirot --skill academic-paper-review명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
SOC 직업 분류 기준
| name | academic-paper-review |
| description | Structured peer-review of academic papers. |
| allowed-tools | ["browse_page","web_search","write_file","present_files"] |
| enabled | true |
| related-skills | ["arxiv","systematic-literature-review","deep-research"] |
| license | MIT |
| author | Adapted from deer-flow (Bytedance, MIT) |
Produces structured, peer-review-quality analyses of academic papers. Follows review standards used by top-tier venues (NeurIPS, ICML, ACL, Nature, IEEE) to provide rigorous, constructive, and balanced assessments.
Covers summary, strengths, weaknesses, methodology assessment, contribution evaluation, literature positioning, and actionable recommendations — all grounded in evidence from the paper itself.
Extract: Title, Authors, Venue/Status, Year, Domain, Paper Type (Empirical / Theoretical / Survey / Systems / Position).
Read the paper systematically using browse_page:
List the paper's main claims explicitly:
Claim 1: [Specific claim]
Evidence: [What evidence supports this]
Strength: [Strong / Moderate / Weak]
Use web_search to understand the research landscape:
"[paper topic] state of the art [current year]"
"[key method name] comparison benchmark"
"[specific technique] limitations criticism"
Use browse_page on key related papers or surveys.
| Criterion | Questions to Ask | Rating |
|---|---|---|
| Soundness | Is the approach technically correct? | 1-5 |
| Novelty | What is genuinely new vs incremental? | 1-5 |
| Reproducibility | Are details sufficient? Code/data available? | 1-5 |
| Experimental Design | Are baselines fair? Ablations adequate? | 1-5 |
| Statistical Rigor | Results significant? Error bars? Multiple runs? | 1-5 |
| Scalability | Does it scale? Computational costs discussed? | 1-5 |
| Level | Description |
|---|---|
| Landmark | Fundamentally changes the field |
| Significant | Strong contribution advancing state of the art |
| Moderate | Useful contribution with some limitations |
| Marginal | Minimal advance over existing work |
| Below threshold | Does not meet publication standards |
Produce the final review using this template:
# 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 core contribution, approach, and main findings.
State overall assessment upfront.]
## Summary of Contributions
1. [First claimed contribution]
2. [Second claimed contribution]
## Strengths
### S1: [Concise strength title]
[Detailed explanation with specific references to sections, figures, tables.]
### S2: [Concise strength title]
[...]
## Weaknesses
### W1: [Concise weakness title]
[Detailed explanation. Explain impact. Suggest how to address.]
### W2: [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]
2. [Question about methodology choices]
## Literature Positioning
[How does this work relate to current state of the art? Key related works cited?]
## Recommendations
**Overall Assessment**: [Accept / Weak Accept / Borderline / Weak Reject / Reject]
**Confidence**: [High / Medium / Low]
**Contribution Level**: [Landmark / Significant / Moderate / Marginal / Below threshold]
### Actionable Suggestions for Improvement
[Specific, constructive suggestion]
[Specific, constructive suggestion]
| Paper Type | Focus Areas |
|---|---|
| Empirical | Experimental design, baselines, statistical significance, ablations |
| Theoretical | Proof correctness, assumption reasonableness, tightness of bounds |
| Survey | Comprehensiveness, taxonomy quality, coverage of recent work |
| Systems | Architecture decisions, scalability evidence, real-world deployment |
| Position | Argument coherence, evidence for claims, impact potential |
.poirot/outputs/review-{paper-topic}.md via write_filepresent_files