literature-review

Conduct systematic literature reviews across academic databases with verified citations and PDF output.

Updated Aug 12, 2026
One-click install
npx skills add https://github.com/littlt-momo-c-yfc/skills --skill literature-review-littlt-momo-c-yfc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: literature-review
Source: https://github.com/littlt-momo-c-yfc/skills/tree/main/skills/scientific-toolkit-skill/references/scientific-skills/literature-review
Command: npx skills add https://github.com/littlt-momo-c-yfc/skills --skill literature-review-littlt-momo-c-yfc

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, pandoc, xelatex, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve? Conducting a rigorous literature review requires searching multiple academic databases, deduplicating results, screening hundreds of papers, verifying every citation, and formatting the final document—an error-prone process that often takes weeks of manual effort. ## Core Features & Use Cases - Multi-Database Search: Query PubMed, bioRxiv, arXiv, Semantic Scholar, and web sources with documented, reproducible search strategies and PRISMA-compliant screening workflows. - Citation Verification: Automatically validate every DOI against CrossRef and generate correctly formatted references in APA, Nature, Vancouver, Chicago, or IEEE styles. - Professional Output: Generate structured markdown reviews from a full template and convert them to publication-ready PDFs via pandoc and xelatex. - Use Case: A graduate student writing a thesis chapter on CRISPR therapies can search PubMed and bioRxiv, deduplicate and rank results by citation count, synthesize findings thematically, verify all DOIs, and export a formatted PDF review. ## Quick Start Ask the agent to conduct a systematic literature review on your research topic, searching PubMed and preprint servers, and produce a verified PDF document.

Frequently Asked Questions about literature-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I conduct a systematic literature review with AI?

Define a research question using the PICO framework, then search at least three databases such as PubMed, bioRxiv, and Semantic Scholar. Screen results through title, abstract, and full-text stages, synthesize findings thematically, and verify all citations before generating the final document.

How to verify DOIs and citations in a research paper?

Run the verify_citations.py script on your markdown file to extract every DOI, check each one against the CrossRef API, and retrieve correct metadata. It produces a verification report listing failed DOIs and generates properly formatted citations in APA or Nature style.

What databases should I search for a biomedical literature review?

Search a minimum of three complementary sources: PubMed for peer-reviewed biomedical literature, bioRxiv or medRxiv for recent preprints, and Semantic Scholar or Google Scholar for cross-disciplinary coverage. Specialized databases like ChEMBL, UniProt, or COSMIC suit domain-specific topics.

Does the PDF generation require additional software?

Yes, PDF generation requires pandoc and a LaTeX engine such as xelatex installed on your system. You can check both dependencies by running generate_pdf.py with the --check-deps flag before converting your markdown review.

Why should literature reviews be organized thematically instead of by study?

Thematic organization synthesizes findings across multiple studies, revealing consensus, contradictions, and research gaps. Study-by-study summaries merely list results without critical analysis, which fails academic review standards and PRISMA guidelines.