| name | review-paper-writing |
| description | Comprehensive guide to writing literature review / survey papers using Claude Code skills, MCP bio-research tools, scientific writing plugins, and 2025-2026 AI research tools (Semantic Scholar, OpenAlex, Elicit, Research Rabbit, Consensus, Scite.ai) |
| version | 2.0 |
| license | Apache-2.0 |
Review Paper Writing
A comprehensive skill for writing literature review and survey papers using Claude Code. Combines MCP bio-research tools for literature search, scientific writing plugins for drafting, AI-powered research tools (2025-2026), and structured workflows for every phase from topic definition to submission.
Quick Start
/plugin marketplace add https://github.com/K-Dense-AI/claude-scientific-writer
/plugin install claude-scientific-writer
/scientific-writer:init
/paper
/bio-research:start
See references/tools-installation.md for detailed tool comparison and installation instructions.
See references/mcp-bio-research.md for MCP tool API reference.
Review Paper Writing Workflow (7 Phases)
Phase 1: Topic Definition & Scope
Goal: Define research questions and scope.
Tools: /paper, Scientific Writing skill
Steps:
- Define 2-3 core research questions
- Identify key terms and synonyms for search
- Set inclusion/exclusion criteria
- Choose review type (narrative, systematic, scoping, meta-analysis)
Phase 2: Literature Search & Collection（增强版）
Goal: Systematically find and collect relevant papers using AI-powered tools.
Tools: PubMed MCP, bioRxiv MCP, Semantic Scholar, OpenAlex, Elicit, Research Rabbit, Connected Papers, Consensus, Scite.ai
主要文献数据库
| 数据库 | 领域 | 特点 |
|---|
| PubMed / MEDLINE | 生物医学 | 3300万+文献，MeSH词汇 |
| Web of Science | 综合 | 引用分析权威 |
| Scopus | 综合 | 欧洲偏重，指标丰富 |
| Google Scholar | 综合 | 覆盖最广，含灰色文献 |
| Semantic Scholar | 综合 | AI语义搜索，200M+论文 |
| OpenAlex | 综合 | 完全开源，250M+文献 |
| Dimensions | 综合 | 含专利和临床试验 |
| IEEE Xplore | 工程/CS | IEEE/IET出版物 |
| ACM Digital Library | CS | ACM出版物 |
| arXiv | CS/物理/数学/生物 | 预印本，最新成果 |
| bioRxiv / medRxiv | 生物医学 | 生物医学预印本 |
| ChemRxiv | 化学 | 化学预印本 |
AI 辅助文献工具（2025-2026最新）
# Semantic Scholar - 语义搜索 + TLDR摘要
访问: https://api.semanticscholar.org/graph/v1/paper/search
特点: 免费API，自动生成TLDR摘要，引用图谱分析
用法: 输入概念性查询，获取语义相似论文
# OpenAlex - 开源学术元数据
访问: https://api.openalex.org/works?search=<query>
特点: 完全免费，250M+文献，机构/概念分析
用法: 系统性检索，支持引用网络分析
# Elicit - AI结构化数据提取
访问: https://elicit.com
特点: 自动提取研究人群、方法、结果等结构化数据
用法: 输入研究问题，自动分析相关论文并提取关键信息
# Research Rabbit - 引用网络映射
访问: https://researchrabbitapp.com
特点: 从种子论文扩展发现相关工作，可视化引用网络
用法: 导入已知关键论文，探索相关论文空间
# Connected Papers - 图谱化文献发现
访问: https://www.connectedpapers.com
特点: 基于引用相似度的图谱化文献关联
用法: 输入核心论文，发现相关文献簇
# Consensus - 科学共识检查
访问: https://consensus.app
特点: 快速了解特定研究问题的学术共识
用法: 输入具体问题，获取文献支持的答案
# Scite.ai - 引用质量验证
访问: https://scite.ai
特点: 区分"支持"/"反驳"/"提及"三类引用关系
用法: 验证关键声明的文献支持度，发现争议性研究
Steps:
- 在主要数据库运行系统性检索（使用标准化检索策略）
- 用 Semantic Scholar 进行语义检索，捕获传统关键词可能遗漏的相关文献
- 用 Research Rabbit 从关键种子论文扩展发现相关工作
- 用 Connected Papers 发现主题相近的文献簇
- 用 Elicit 自动提取结构化数据（人群、方法、结果）
- 用 Scite.ai 验证关键引用的可靠性
- 检查 arXiv/bioRxiv 获取最新预印本成果
- 导出引用并按主题分类整理
See Multi-Database Search Workflow for detailed steps.
Phase 3: Literature Organization & Synthesis
Goal: Read, categorize, and synthesize findings.
Tools: Literature Review skill, Citation Management skill, PDF skill
Steps:
- Organize papers by theme (NOT by individual study)
- Create a comparison matrix (see Paper Comparison Matrix template)
- Identify consensus, contradictions, and gaps
- Build citation database (BibTeX format)
Key Principles:
- Synthesize across studies, compare and contrast
- Critically evaluate quality and consistency
- Note what is missing or understudied
- Track how the field has evolved over time
Phase 4: Outline & Structure
Goal: Create a detailed outline.
Tools: Scientific Writing skill, Academic Writing Standards skill
Phase 5: Writing
Goal: Draft the full paper.
Tools: Scientific Writer CLI/Plugin, Content Research Writer
Tips:
- Write one section at a time
- Use active voice where possible
- Ensure every claim has a citation
- Maintain consistent terminology throughout
Phase 6: Review & Refinement
Goal: Polish to publication quality.
Tools: Peer Review skill, Scholar Evaluation skill (8-dimension scoring), Academic Writing Standards
Steps:
- Run peer review evaluation
- Check citation completeness and accuracy
- Verify all figures and tables are referenced
- Ensure logical flow between sections
- Check for redundancy and gaps
- Polish language and formatting
Phase 7: Formatting & Submission
Goal: Format for target venue and prepare submission.
Tools: Scientific Writer venue templates, LaTeX Research Posters skill, Scientific Slides skill
Steps:
- Select target journal/conference template
- Format according to submission guidelines
- Prepare cover letter
- Generate supplementary materials if needed
- Final proofreading
Scientific Writer Skills Reference (16+)
Writing & Research
| # | Skill | Purpose |
|---|
| 1 | Scientific Writing | IMRaD structure, citation styles, figure/table formatting, reporting standards |
| 2 | Literature Review | Cross-database search, citation organization, thematic synthesis, gap identification |
| 3 | Peer Review | Manuscript evaluation, methodology assessment, journal compliance |
| 4 | Scholar Evaluation | 8-dimension scoring (originality, methodology, clarity, significance, technical soundness, presentation, reproducibility, impact) |
| 5 | Research Grants | NSF/NIH/DOE/DARPA proposals, budget templates |
| 6 | Clinical Reports | CARE-compliant case reports, HIPAA compliance |
| 7 | Clinical Decision Support | GRADE framework, treatment plans, cohort analyses |
| 8 | Market Research Reports | Market sizing, competitive landscapes |
Presentation & Visual
| # | Skill | Purpose |
|---|
| 9 | LaTeX Research Posters | beamerposter/tikzposter frameworks |
| 10 | Scientific Slides | 5-60 min talks, timing guidance, AI visuals |
| 11 | Scientific Schematics | TikZ publication-quality figures and flowcharts |
Document Manipulation
| # | Skill | Purpose |
|---|
| 12 | MarkItDown | PDF/DOCX/PPTX/XLSX/images to Markdown |
| 13 | DOCX | Word document processing |
| 14 | PDF | PDF extraction and generation |
| 15 | PPTX | PowerPoint creation and editing |
| 16 | XLSX | Spreadsheet data and analysis |
Recommended Skill Combination by Phase
Phase 1 (Topic & Scope): Scientific Writing
Phase 2 (Search): Literature Review + Bio-Research MCP + Semantic Scholar + Elicit
Phase 3 (Organize): Citation Management + Literature Review
Phase 4 (Outline): Scientific Writing + Academic Writing Standards
Phase 5 (Write): Scientific Writing + Literature Review
Phase 6 (Review): Peer Review + Scholar Evaluation + Scite.ai
Phase 7 (Format): Scientific Writing (venue templates)
Templates & Checklists
Systematic Review Structure（PRISMA 2020 Updated）
PRISMA 2020 是目前最新的系统综述报告规范，相比2009版有重要更新：
- 新增数据库以外来源（citation searching, grey literature）的报告
- 更新流程图（现包含4个阶段：Identification, Screening, Eligibility, Included）
- 增加偏倚风险评估要求
1. Title
- PRISMA 2020 compliant title (include "systematic review" or "meta-analysis")
2. Abstract (structured: background, objectives, eligibility criteria,
information sources, risk of bias, synthesis methods, results, limitations,
conclusions, systematic review registration)
3. Introduction
- Rationale
- Objectives
- Research questions (PICO format)
4. Methods
- Eligibility criteria (PICO + study design)
- Information sources (all databases + dates searched)
- Search strategy (full search strategy for at least one database)
- Selection process (screening steps, software used)
- Data extraction process
- Study risk of bias assessment (tool used, e.g., RoB 2, ROBINS-I)
- Effect measures
- Synthesis methods (narrative/quantitative)
- Reporting bias assessment
- Certainty of evidence (e.g., GRADE)
5. Results
- Study selection (PRISMA 2020 flow diagram with 4 phases)
- Study characteristics
- Risk of bias in studies
- Results of individual studies
- Results of syntheses
- Reporting biases
- Certainty of evidence
6. Discussion
- Summary of evidence
- Limitations
- Implications
7. Other information
- Registration and protocol
- Support/funding
- Competing interests
8. References
Meta-Analysis 工作流
from pymare import Dataset
import numpy as np
def cohens_d(mean1, mean2, sd1, sd2, n1, n2):
"""计算Cohen's d效应量
Args:
mean1: 干预组/实验组均值
mean2: 对照组均值
sd1: 干预组标准差
sd2: 对照组标准差
n1: 干预组样本量
n2: 对照组样本量
Returns:
float: Cohen's d效应量（正值表示干预组更高）
"""
pooled_sd = np.sqrt(((n1-1)*sd1**2 + (n2-1)*sd2**2) / (n1+n2-2))
return (mean1 - mean2) / pooled_sd
import forestplot as fp
fp.forestplot(
df,
estimate='effect_size',
ll='lower_ci',
hl='upper_ci',
varlabel='study',
xlabel='Effect Size (Cohen\'s d)',
annote=['n', 'p_value'],
annoteheaders=['N', 'P-value'],
rightannote=['weight'],
right_annoteheaders=['Weight (%)'],
figsize=(8, 6)
)
library(meta)
library(metafor)
meta_result <- metacont(
n.e = n_treatment,
mean.e = mean_treatment,
sd.e = sd_treatment,
n.c = n_control,
mean.c = mean_control,
sd.c = sd_control,
studlab = study_label,
data = meta_data,
sm = "SMD",
method.tau = "REML"
)
forest(meta_result, sortvar = TE)
funnel(meta_result)
metabias(meta_result, method.bias = "linreg")
print(meta_result$I2)
print(meta_result$Q)
Narrative Review Structure
1. Title
2. Abstract
3. Introduction
- Background
- Scope and purpose
4. Body (thematic sections)
- Theme 1: [Topic]
- Current state of knowledge
- Key findings across studies
- Contradictions and debates
- Theme 2: [Topic]
- Theme 3: [Topic]
5. Discussion
- Synthesis of findings
- Research gaps identified
- Methodological challenges
- Future directions
6. Conclusion
7. References
Literature Search Strategy Template
## Search Terms
Primary terms: [term1], [term2], [term3]
Secondary terms: [term4], [term5]
Boolean operators: (term1 OR term2) AND (term3 OR term4)
## Databases to Search
- [ ] PubMed / MEDLINE
- [ ] Web of Science
- [ ] Scopus
- [ ] Google Scholar
- [ ] Semantic Scholar
- [ ] OpenAlex
- [ ] arXiv (preprints: CS/Physics/Math/Biology)
- [ ] bioRxiv / medRxiv (biomedical preprints)
- [ ] IEEE Xplore (engineering/CS)
- [ ] ACM Digital Library (CS)
- [ ] Dimensions
- [ ] Domain-specific databases
## Inclusion Criteria
- Publication date: [start] to [end]
- Language: [languages]
- Study type: [types]
- Population: [if applicable]
## Exclusion Criteria
- [criterion 1]
- [criterion 2]
## Search Record
| Database | Date | Query | Results | After Dedup | Selected |
|----------|------|-------|---------|-------------|----------|
| PubMed | | | | | |
| Semantic Scholar | | | | | |
| arXiv | | | | | |
Paper Comparison Matrix
| # | Author(s) | Year | Title | Method | Sample/Data | Key Findings | Limitations | Quality |
|---|-----------|------|-------|--------|-------------|--------------|-------------|---------|
| 1 | | | | | | | | H/M/L |
| 2 | | | | | | | | H/M/L |
Quality: H = High, M = Medium, L = Low
Academic Writing Checklist
Structure:
Language:
Citations:
Figures & Tables:
Common Mistakes to Avoid:
- Plagiarism (even unintentional)
- Over-reliance on a single source
- Citation clusters without synthesis
- Listing studies without comparing them
- Missing recent publications (last 2-3 years)
- Ignoring contradictory evidence
AI 辅助综述伦理指南
AI辅助文献综述的使用规范（2025-2026）
允许的AI辅助用途
- 文献检索辅助（Semantic Scholar, Elicit等）
- 论文摘要理解（SciSpace等）
- 写作润色和语法纠错
- 格式规范化
必须由人工完成的工作
- 文献纳入/排除决策（必须基于研究者判断）
- 数据提取的准确性验证（AI提取数据必须人工核实）
- 结果解读和分析综合
- 结论的形成
透明披露要求
- 说明使用了哪些AI辅助工具
- 描述AI在文献筛选/数据提取中的具体角色
- 按目标期刊政策进行适当披露（参考COPE指南）
引用验证
- 禁止将AI生成的虚假引用纳入综述
- 使用Scite.ai验证关键引用的支持关系
- 对争议性声明进行原文核查
Citation Style Quick Reference
APA 7th Edition:
In-text: (Author, Year) or Author (Year)
Reference: Author, A. A. (Year). Title. Journal, Volume(Issue), Pages. https://doi.org/xxx
IEEE:
In-text: [1], [2], [3]
Reference: [1] A. Author, "Title," Journal, vol. X, no. Y, pp. Z-Z, Month Year.
Nature:
In-text: Superscript numbers: text^1
Reference: 1. Author, A. A. Title. Journal Vol, Pages (Year).
Chicago (Author-Date):
In-text: (Author Year, Page)
Reference: Author, First. Year. "Title." Journal Volume (Issue): Pages.
