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Agent Skill · 待分类

literature-review(文献综述)

literature-review 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

literature-review 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为权限未标注;许可证为 MIT,暂无第三方扫描结果,按安装量在待分类类的 11,209 个 Skill 里排第 2,971。

总安装 1,248周安装 52GitHub Stars 14下载 416核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:literature-review(文献综述)
来源仓库:https://github.com/jackspace/claudeskillz
仓库路径:skills/literature-review
安装命令:
npx skills add https://github.com/jackspace/claudeskillz --skill literature-review
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jackspace/claudeskillz --skill literature-review

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

literature-review 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合围绕项目状态与变更进行整理。适用于需要围绕仓库状态、代码变更或协作事项进行信息组织的场景。可结合来源仓库、安装命令和原始 README 继续核验具体用法与功能细节。

安装命令为 npx skills add https://github.com/jackspace/claudeskillz --skill literature-review。使用前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

来源仓库内路径:skills/literature-review

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jackspace/claudeskillz --skill literature-revi…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    权限没有明确标注,第一次使用时只给一个无关紧要的任务,观察它到底读了哪些文件和网络。

常见问题

6 条

literature-review 怎么安装?

在终端执行 npx skills add https://github.com/jackspace/claudeskillz --skill literature-review。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

literature-review 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

literature-review 需要什么权限?

权限级别没有明确标注。第一次使用时建议只给无关紧要的任务,观察它实际读写了哪些内容。

literature-review 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

literature-review 用的人多吗?

公开数据是累计安装 1,248 次,近一周安装 52 次,下载 416 次,GitHub 14 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

literature-review 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
literature-review

文献综述 · 本页

1,24814权限未标注MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Literature Review

Overview

Conduct systematic, comprehensive literature reviews following rigorous academic methodology. Search multiple literature databases, synthesize findings thematically, verify all citations for accuracy, and generate professional output documents in markdown and PDF formats.

This skill integrates with multiple scientific skills for database access (gget, bioservices, datacommons-client) and provides specialized tools for citation verification, result aggregation, and document generation.

When to Use This Skill

Use this skill when:

  • Conducting a systematic literature review for research or publication
  • Synthesizing current knowledge on a specific topic across multiple sources
  • Performing meta-analysis or scoping reviews
  • Writing the literature review section of a research paper or thesis
  • Investigating the state of the art in a research domain
  • Identifying research gaps and future directions
  • Requiring verified citations and professional formatting

Core Workflow

Literature reviews follow a structured, multi-phase workflow:

Phase 1: Planning and Scoping

  1. Define Research Question: Use PICO framework (Population, Intervention, Comparison, Outcome) for clinical/biomedical reviews

- Example: "What is the efficacy of CRISPR-Cas9 (I) for treating sickle cell disease (P) compared to standard care (C)?"

  1. Establish Scope and Objectives:

- Define clear, specific research questions - Determine review type (narrative, systematic, scoping, meta-analysis) - Set boundaries (time period, geographic scope, study types)

  1. Develop Search Strategy:

- Identify 2-4 main concepts from research question - List synonyms, abbreviations, and related terms for each concept - Plan Boolean operators (AND, OR, NOT) to combine terms - Select minimum 3 complementary databases

  1. Set Inclusion/Exclusion Criteria:

- Date range (e.g., last 10 years: 2015-2024) - Language (typically English, or specify multilingual) - Publication types (peer-reviewed, preprints, reviews) - Study designs (RCTs, observational, in vitro, etc.) - Document all criteria clearly

Phase 2: Systematic Literature Search

  1. Multi-Database Search: Select databases appropriate for the domain: Biomedical & Life Sciences: General Scientific Literature: Specialized Databases:

- Use gget skill: gget search pubmed "search terms" for PubMed/PMC - Use gget skill: gget search biorxiv "search terms" for preprints - Use bioservices skill for ChEMBL, KEGG, UniProt, etc. - Search arXiv via direct API (preprints in physics, math, CS, q-bio) - Search Semantic Scholar via API (200M+ papers, cross-disciplinary) - Use Google Scholar for comprehensive coverage (manual or careful scraping) - Use gget alphafold for protein structures - Use gget cosmic for cancer genomics - Use datacommons-client for demographic/statistical data - Use specialized databases as appropriate for the domain

  1. Document Search Parameters: ## Search Strategy ### Database: PubMed - **Date searched**: 2024-10-25 - **Date range**: 2015-01-01 to 2024-10-25 - **Search string**: ("CRISPR"[Title] OR "Cas9"[Title]) AND ("sickle cell"[MeSH] OR "SCD"[Title/Abstract]) AND 2015:2024[Publication Date] - **Results**: 247 articles Repeat for each database searched.
  2. Export and Aggregate Results:

- Export results in JSON format from each database - Combine all results into a single file - Use scripts/search_databases.py for post-processing: python search_databases.py combined_results.json \ --deduplicate \ --format markdown \ --output aggregated_results.md

Phase 3: Screening and Selection

  1. Deduplication: python search_databases.py results.json --deduplicate --output unique_results.json

- Removes duplicates by DOI (primary) or title (fallback) - Document number of duplicates removed

  1. Title Screening:

- Review all titles against inclusion/exclusion criteria - Exclude obviously irrelevant studies - Document number excluded at this stage

  1. Abstract Screening:

- Read abstracts of remaining studies - Apply inclusion/exclusion criteria rigorously - Document reasons for exclusion

  1. Full-Text Screening:

- Obtain full texts of remaining studies - Conduct detailed review against all criteria - Document specific reasons for exclusion - Record final number of included studies

  1. Create PRISMA Flow Diagram: Initial search: n = X ├─ After deduplication: n = Y ├─ After title screening: n = Z ├─ After abstract screening: n = A └─ Included in review: n = B

Phase 4: Data Extraction and Quality Assessment

  1. Extract Key Data from each included study:

- Study metadata (authors, year, journal, DOI) - Study design and methods - Sample size and population characteristics - Key findings and results - Limitations noted by authors - Funding sources and conflicts of interest

  1. Assess Study Quality:

- For RCTs: Use Cochrane Risk of Bias tool - For observational studies: Use Newcastle-Ottawa Scale - For systematic reviews: Use AMSTAR 2 - Rate each study: High, Moderate, Low, or Very Low quality - Consider excluding very low-quality studies

  1. Organize by Themes:

- Identify 3-5 major themes across studies - Group studies by theme (studies may appear in multiple themes) - Note patterns, consensus, and controversies

Phase 5: Synthesis and Analysis

  1. Create Review Document from template: cp assets/review_template.md my_literature_review.md
  2. Write Thematic Synthesis (NOT study-by-study summaries): Example structure: #### 3.3.1 Theme: CRISPR Delivery Methods Multiple delivery approaches have been investigated for therapeutic gene editing. Viral vectors (AAV) were used in 15 studies^1-15^ and showed high transduction efficiency (65-85%) but raised immunogenicity concerns^3,7,12^. In contrast, lipid nanoparticles demonstrated lower efficiency (40-60%) but improved safety profiles^16-23^.

- Organize Results section by themes or research questions - Synthesize findings across multiple studies within each theme - Compare and contrast different approaches and results - Identify consensus areas and points of controversy - Highlight the strongest evidence

  1. Critical Analysis:

- Evaluate methodological strengths and limitations across studies - Assess quality and consistency of evidence - Identify knowledge gaps and methodological gaps - Note areas requiring future research

  1. Write Discussion:

- Interpret findings in broader context - Discuss clinical, practical, or research implications - Acknowledge limitations of the review itself - Compare with previous reviews if applicable - Propose specific future research directions

Phase 6: Citation Verification

CRITICAL: All citations must be verified for accuracy before final submission.

  1. Verify All DOIs: python scripts/verify_citations.py my_literature_review.md This script:

- Extracts all DOIs from the document - Verifies each DOI resolves correctly - Retrieves metadata from CrossRef - Generates verification report - Outputs properly formatted citations

  1. Review Verification Report:

- Check for any failed DOIs - Verify author names, titles, and publication details match - Correct any errors in the original document - Re-run verification until all citations pass

  1. Format Citations Consistently:

- Choose one citation style and use throughout (see references/citation_styles.md) - Common styles: APA, Nature, Vancouver, Chicago, IEEE - Use verification script output to format citations correctly - Ensure in-text citations match reference list format

Phase 7: Document Generation

  1. Generate PDF: python scripts/generate_pdf.py my_literature_review.md \ --citation-style apa \ --output my_review.pdf Options:

- --citation-style: apa, nature, chicago, vancouver, ieee - --no-toc: Disable table of contents - --no-numbers: Disable section numbering - --check-deps: Check if pandoc/xelatex are installed

  1. Review Final Output:

- Check PDF formatting and layout - Verify all sections are present - Ensure citations render correctly - Check that figures/tables appear properly - Verify table of contents is accurate

  1. Quality Checklist:

- All DOIs verified with verify_citations.py - Citations formatted consistently - PRISMA flow diagram included (for systematic reviews) - Search methodology fully documented - Inclusion/exclusion criteria clearly stated - Results organized thematically (not study-by-study) - Quality assessment completed - Limitations acknowledged - References complete and accurate - PDF generates without errors

Database-Specific Search Guidance

PubMed / PubMed Central

Access via gget skill:

# Search PubMed
gget search pubmed "CRISPR gene editing" -l 100

# Search with filters
# Use PubMed Advanced Search Builder to construct complex queries
# Then execute via gget or direct Entrez API

Search tips:

  • Use MeSH terms: "sickle cell disease"[MeSH]
  • Field tags: [Title], [Title/Abstract], [Author]
  • Date filters: 2020:2024[Publication Date]
  • Boolean operators: AND, OR, NOT
  • See MeSH browser: https://meshb.nlm.nih.gov/search

bioRxiv / medRxiv

Access via gget skill:

gget search biorxiv "CRISPR sickle cell" -l 50

Important considerations:

  • Preprints are not peer-reviewed
  • Verify findings with caution
  • Check if preprint has been published (CrossRef)
  • Note preprint version and date

arXiv

Access via direct API or WebFetch:

# Example search categories:
# q-bio.QM (Quantitative Methods)
# q-bio.GN (Genomics)
# q-bio.MN (Molecular Networks)
# cs.LG (Machine Learning)
# stat.ML (Machine Learning Statistics)

# Search format: category AND terms
search_query = "cat:q-bio.QM AND ti:\"single cell sequencing\""

Semantic Scholar

Access via direct API (requires API key, or use free tier):

  • 200M+ papers across all fields
  • Excellent for cross-disciplinary searches
  • Provides citation graphs and paper recommendations
  • Use for finding highly influential papers

Specialized Biomedical Databases

Use appropriate skills:

  • ChEMBL: bioservices skill for chemical bioactivity
  • UniProt: gget or bioservices skill for protein information
  • KEGG: bioservices skill for pathways and genes
  • COSMIC: gget skill for cancer mutations
  • AlphaFold: gget alphafold for protein structures
  • PDB: gget or direct API for experimental structures

Citation Chaining

Expand search via citation networks:

  1. Forward citations (papers citing key papers):

- Use Google Scholar "Cited by" - Use Semantic Scholar or OpenAlex APIs - Identifies newer research building on seminal work

  1. Backward citations (references from key papers):

- Extract references from included papers - Identify highly cited foundational work - Find papers cited by multiple included studies

Citation Style Guide

Detailed formatting guidelines are in references/citation_styles.md. Quick reference:

APA (7th Edition)

  • In-text: (Smith et al., 2023)
  • Reference: Smith, J. D., Johnson, M. L., & Williams, K. R. (2023). Title. *Journal*, *22*(4), 301-318. https://doi.org/10.xxx/yyy

Nature

  • In-text: Superscript numbers^1,2^
  • Reference: Smith, J. D., Johnson, M. L. & Williams, K. R. Title. *Nat. Rev. Drug Discov.* 22, 301-318 (2023).

Vancouver

  • In-text: Superscript numbers^1,2^
  • Reference: Smith JD, Johnson ML, Williams KR. Title. Nat Rev Drug Discov. 2023;22(4):301-18.

Always verify citations with verify_citations.py before finalizing.

Best Practices

Search Strategy

  1. Use multiple databases (minimum 3): Ensures comprehensive coverage
  2. Include preprint servers: Captures latest unpublished findings
  3. Document everything: Search strings, dates, result counts for reproducibility
  4. Test and refine: Run pilot searches, review results, adjust search terms

Screening and Selection

  1. Use clear criteria: Document inclusion/exclusion criteria before screening
  2. Screen systematically: Title → Abstract → Full text
  3. Document exclusions: Record reasons for excluding studies
  4. Consider dual screening: For systematic reviews, have two reviewers screen independently

Synthesis

  1. Organize thematically: Group by themes, NOT by individual studies
  2. Synthesize across studies: Compare, contrast, identify patterns
  3. Be critical: Evaluate quality and consistency of evidence
  4. Identify gaps: Note what's missing or understudied

Quality and Reproducibility

  1. Assess study quality: Use appropriate quality assessment tools
  2. Verify all citations: Run verify_citations.py script
  3. Document methodology: Provide enough detail for others to reproduce
  4. Follow guidelines: Use PRISMA for systematic reviews

Writing

  1. Be objective: Present evidence fairly, acknowledge limitations
  2. Be systematic: Follow structured template
  3. Be specific: Include numbers, statistics, effect sizes where available
  4. Be clear: Use clear headings, logical flow, thematic organization

Common Pitfalls to Avoid

  1. Single database search: Misses relevant papers; always search multiple databases
  2. No search documentation: Makes review irreproducible; document all searches
  3. Study-by-study summary: Lacks synthesis; organize thematically instead
  4. Unverified citations: Leads to errors; always run verify_citations.py
  5. Too broad search: Yields thousands of irrelevant results; refine with specific terms
  6. Too narrow search: Misses relevant papers; include synonyms and related terms
  7. Ignoring preprints: Misses latest findings; include bioRxiv, medRxiv, arXiv
  8. No quality assessment: Treats all evidence equally; assess and report quality
  9. Publication bias: Only positive results published; note potential bias
  10. Outdated search: Field evolves rapidly; clearly state search date

Example Workflow

Complete workflow for a biomedical literature review:

# 1. Create review document from template
cp assets/review_template.md crispr_sickle_cell_review.md

# 2. Search multiple databases using appropriate skills
# - Use gget skill for PubMed, bioRxiv
# - Use direct API access for arXiv, Semantic Scholar
# - Export results in JSON format

# 3. Aggregate and process results
python scripts/search_databases.py combined_results.json \
  --deduplicate \
  --rank citations \
  --year-start 2015 \
  --year-end 2024 \
  --format markdown \
  --output search_results.md \
  --summary

# 4. Screen results and extract data
# - Manually screen titles, abstracts, full texts
# - Extract key data into the review document
# - Organize by themes

# 5. Write the review following template structure
# - Introduction with clear objectives
# - Detailed methodology section
# - Results organized thematically
# - Critical discussion
# - Clear conclusions

# 6. Verify all citations
python scripts/verify_citations.py crispr_sickle_cell_review.md

# Review the citation report
cat crispr_sickle_cell_review_citation_report.json

# Fix any failed citations and re-verify
python scripts/verify_citations.py crispr_sickle_cell_review.md

# 7. Generate professional PDF
python scripts/generate_pdf.py crispr_sickle_cell_review.md \
  --citation-style nature \
  --output crispr_sickle_cell_review.pdf

# 8. Review final PDF and markdown outputs

Integration with Other Skills

This skill works seamlessly with other scientific skills:

Database Access Skills

  • gget: PubMed, bioRxiv, COSMIC, AlphaFold, Ensembl, UniProt
  • bioservices: ChEMBL, KEGG, Reactome, UniProt, PubChem
  • datacommons-client: Demographics, economics, health statistics

Analysis Skills

  • pydeseq2: RNA-seq differential expression (for methods sections)
  • scanpy: Single-cell analysis (for methods sections)
  • anndata: Single-cell data (for methods sections)
  • biopython: Sequence analysis (for background sections)

Visualization Skills

  • matplotlib: Generate figures and plots for review
  • seaborn: Statistical visualizations

Writing Skills

  • brand-guidelines: Apply institutional branding to PDF
  • internal-comms: Adapt review for different audiences

Resources

Bundled Resources

Scripts:

  • scripts/verify_citations.py: Verify DOIs and generate formatted citations
  • scripts/generate_pdf.py: Convert markdown to professional PDF
  • scripts/search_databases.py: Process, deduplicate, and format search results

References:

  • references/citation_styles.md: Detailed citation formatting guide (APA, Nature, Vancouver, Chicago, IEEE)
  • references/database_strategies.md: Comprehensive database search strategies

Assets:

  • assets/review_template.md: Complete literature review template with all sections

External Resources

Guidelines:

Tools:

Citation Styles:

Dependencies

Required Python Packages

pip install requests  # For citation verification

Required System Tools

# For PDF generation
brew install pandoc  # macOS
apt-get install pandoc  # Linux

# For LaTeX (PDF generation)
brew install --cask mactex  # macOS
apt-get install texlive-xetex  # Linux

Check dependencies:

python scripts/generate_pdf.py --check-deps

Summary

This literature-review skill provides:

  1. Systematic methodology following academic best practices
  2. Multi-database integration via existing scientific skills
  3. Citation verification ensuring accuracy and credibility
  4. Professional output in markdown and PDF formats
  5. Comprehensive guidance covering the entire review process
  6. Quality assurance with verification and validation tools
  7. Reproducibility through detailed documentation requirements

Conduct thorough, rigorous literature reviews that meet academic standards and provide comprehensive synthesis of current knowledge in any domain.

平台分布

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3.32%
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安全审计

暂无安全审计结果可展示。

权限和风险

权限未标注

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

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