literature-review
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).
npx skills add majiayu000/claude-skill-registry --skill scientific-thinking-literature-review-jackspace-claudeskillz-4c7 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Conveys a structured process for performing systematic literature reviews across multiple databases, including planning, searching, screening, data extraction, synthesis, citation verification, and document generation. It emphasizes generating outputs in markdown and PDF with verified citations in various styles.
How it works
- Define the research question and scope, choosing review type and boundaries.
- Develop a search strategy across databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.) and document search parameters for each database.
- Export results in JSON format from each database and aggregate them into a single file; use a provided script for post-processing to produce a markdown output.
- Screen results in phases: deduplication, title screening, abstract screening, full-text screening; document exclusions and final inclusions.
- Create a PRISMA-like flow diagram showing counts at each stage.
- Extract data (metadata, study design, sample size, results, limitations, funding, COI) and assess study quality with established tools appropriate to study type.
- Organize findings thematically (3-5 themes) and perform a thematic synthesis rather than study-by-study summaries.
- Write a discussion interpreting findings, acknowledging limitations, and suggesting future directions.
- Verify all citations with a script that checks DOIs, retrieves metadata, and outputs formatted citations; re-run until all pass.
- Generate a PDF from the markdown using a specified citation style; provide options for TOC, numbering, and dependencies and verify final formatting.
When to use it
Use this skill for systematic literature reviews, meta-analyses, research synthesis, scoping reviews, or comprehensive literature searches requiring verified citations and professional formatting across biomedical, scientific, and technical domains.
What it can touch
- Interfaces with tools and scripts for processing results:
scripts/search_databases.py,scripts/verify_citations.py,assets/review_template.md, andpythoncommands. - Outputs include markdown files and PDFs formatted to chosen citation styles (APA, Nature, Vancouver, etc.).
Caveats
- All citations must be verified for accuracy before final submission using the verification script.
- The workflow expects multi-database access (including PubMed, bioRxiv, arXiv, Semantic Scholar) and may rely on integration with tools like gget, bioservices, and datacommons-client as referenced in the workflow.
# 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, Compari
- Overview
- When to Use This Skill
- Core Workflow
- Phase 1: Planning and Scoping
- Phase 2: Systematic Literature Search
- Phase 3: Screening and Selection
- Phase 4: Data Extraction and Quality Assessment
- Phase 5: Synthesis and Analysis
- Phase 6: Citation Verification
- Phase 7: Document Generation
- Database-Specific Search Guidance
- PubMed / PubMed Central
- bioRxiv / medRxiv
- arXiv
python search_databases.py combined_results.json \ python search_databases.py results.json --deduplicate --output unique_results.json cp assets/review_template.md my_literature_review.md python scripts/verify_citations.py my_literature_review.md python scripts/generate_pdf.py my_literature_review.md \ 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
What does the literature-review skill do?
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill scientific-thinking-literature-review-jackspace-claudeskillz-4c7 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.