academic-paper-review
bytedance/deer-flow · Agent Skill
Анализирует, критикует и обобщает научные статьи, предоставляя структурированные отзывы с оценкой методологии, вклада и рекомендациями.
Перейти к установке ↓Обзор
| Автор | |
|---|---|
| Репозиторий | bytedance/deer-flow ↗ |
| Папка скилла | academic-paper-review |
| Звёзды | 82 309 |
| Файлы | 1 |
| Лицензия | MIT |
| Обновлён | 4 апреля 2026 г. |
| Ссылки | Исходник скилла ↗ · Репозиторий ↗ |
Проверка Mozgi
Что мы нашли в файлах скилла. Подробности — по подписке.
Установка
Скилл — это папка с файлом SKILL.md. Выберите своего агента и скопируйте команды в терминал (macOS, Linux или Git Bash на Windows) в корне проекта.
Скопируйте промпт и вставьте в Claude, Codex или другого ассистента: он сам проверит скилл и подключит его.
Установи мне скилл «academic-paper-review» с mozgi.io (https://mozgi.io/skills/academic-paper-review/). 1. Скачай архив: https://mozgi.io/skills/academic-paper-review/download Если не скачивается — возьми папку скилла из исходника: https://github.com/bytedance/deer-flow/tree/main/skills/public/academic-paper-review 2. Прочитай SKILL.md и остальные файлы. Проверь, что скилл безопасен: нет скрытых команд, отправки данных наружу или скриптов, которые делают не то, что описано. Если что-то подозрительно — остановись и скажи мне. 3. Положи папку «academic-paper-review» в папку скиллов своего агента: .claude/skills/ для Claude Code, .agents/skills/ для Codex, .cursor/skills/ для Cursor, .gemini/skills/ для Gemini CLI. В проекте — внутри проекта, иначе в домашней папке (~/.claude/skills/ и т. п.). 4. Убедись, что получилось <папка скиллов>/academic-paper-review/SKILL.md. 5. Коротко расскажи, что умеет этот скилл, и предложи попробовать его на моей задаче. Если какой-то шаг не можешь сделать сам — подскажи, что нажать или ввести.
git clone --depth 1 --branch main https://github.com/bytedance/deer-flow.git /tmp/deer-flow mkdir -p .claude/skills cp -r /tmp/deer-flow/skills/public/academic-paper-review .claude/skills/academic-paper-review
Перезапустите Claude Code — скилл появится в списке, вызвать вручную: /academic-paper-review. Для всех проектов сразу — папка ~/.claude/skills.
git clone --depth 1 --branch main https://github.com/bytedance/deer-flow.git /tmp/deer-flow mkdir -p .agents/skills cp -r /tmp/deer-flow/skills/public/academic-paper-review .agents/skills/academic-paper-review
Codex ищет скиллы в .agents/skills от текущей папки до корня репозитория; вызвать вручную — /skills или $academic-paper-review. Для всех проектов — ~/.agents/skills.
git clone --depth 1 --branch main https://github.com/bytedance/deer-flow.git /tmp/deer-flow mkdir -p .cursor/skills cp -r /tmp/deer-flow/skills/public/academic-paper-review .cursor/skills/academic-paper-review
Cursor подхватит скилл при запуске; вызвать вручную — «/» в чате агента. Cursor также читает .claude/skills и .agents/skills. Для всех проектов — ~/.cursor/skills.
git clone --depth 1 --branch main https://github.com/bytedance/deer-flow.git /tmp/deer-flow mkdir -p .gemini/skills cp -r /tmp/deer-flow/skills/public/academic-paper-review .gemini/skills/academic-paper-review
Gemini CLI сам предложит включить скилл, когда задача подходит, — вы подтверждаете. Для всех проектов — ~/.gemini/skills.
Просмотрите SKILL.md и сопутствующие файлы перед установкой. Клик по файлу — предпросмотр.
Содержимое SKILL.md
Оригинальный текст автора · только чтениеAcademic 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:
Claim 1: [Specific claim about contribution or finding]
Evidence: [What evidence supports this claim in the paper]
Strength: [Strong / Moderate / Weak]
Claim 2: [...]
...
Phase 2: Critical Analysis
Step 2.1: Literature Context Search
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.
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
# 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]
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}.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")
Вопросы и ответы
Что делает скилл academic-paper-review?
Анализирует, критикует и обобщает научные статьи, предоставляя структурированные отзывы с оценкой методологии, вклада и рекомендациями.
Как установить academic-paper-review?
Откройте блок «Установка» на этой странице и выберите своего агента — Claude Code, Codex, Cursor или Gemini CLI: там готовые команды, которые копируют папку скилла в нужное место. Либо скопируйте промпт из вкладки «Через ассистента» — ассистент сам проверит и подключит скилл.
С какими нейросетями работает academic-paper-review?
Скиллы — это обычные инструкции в Markdown (формат Agent Skills), поэтому academic-paper-review подходит любому агенту, который читает SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode и другие. Модель загружает инструкции только когда задача подходит под описание скилла.
Скилл academic-paper-review бесплатный?
Скилл опубликован автором bytedance в открытом доступе под лицензией MIT. Сам скилл ничего не стоит — вы платите только своему провайдеру нейросети за использованные токены.
Безопасно ли устанавливать скиллы?
Скилл — это инструкции, которые агент будет выполнять, поэтому перед установкой прочитайте SKILL.md и сопутствующие файлы. Скрипты из папки скилла запускаются только если их запустит агент — следите за тем, что он делает, и не давайте лишних прав.
Чем скилл отличается от MCP-сервера или плагина?
MCP-сервер и плагин дают модели новые инструменты — код, который выполняется и возвращает результат. Скилл даёт знания и порядок действий: как подходить к задаче, какие шаги делать и как выглядит хороший результат. Ему не нужен сервер или ключ API.