literature-review

Identify and synthesize research literature from multiple databases into citation-verified reviews in Markdown and PDF formats.

321|26|Updated Mar 10, 2026
One-click install
npx skills add https://github.com/mkurman/tamux --skill literature-review-mkurman
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: literature-review
Source: https://github.com/mkurman/tamux/tree/main/skills/scientific-skills/literature-review
Command: npx skills add https://github.com/mkurman/tamux --skill literature-review-mkurman

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Systematic, rigorous literature reviews are essential for credible knowledge synthesis but are time-consuming and hard to reproduce. This skill provides a structured methodology and tooling to plan, search across multiple databases, screen studies, extract data, assess quality, synthesize findings, and verify citations, delivering a complete, auditable review workflow.

Core Features & Use Cases

  • Structured planning and scoping using predefined templates and best-practice protocols (PRISMA, AMSTAR 2).
  • Multi-database search orchestration across PubMed, bioRxiv/medRxiv, arXiv, Semantic Scholar, and other sources with documentation of strings, dates, and results.
  • Systematic screening and data extraction with transparent decision logs and quality assessment.
  • Automated citation verification and bibliographic formatting to ensure accuracy in outputs.
  • Output generation in Markdown and export-ready PDF formats using included templates and assets.

Quick Start

Copy assets/review_template.md to your project, rename it to your topic (e.g., crispr_sickle_cell_review.md), and begin the multi-phase literature-review workflow.

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 across multiple databases?

A systematic literature review searches across databases like PubMed, arXiv, and Semantic Scholar, then deduplicates, screens, and synthesizes findings. This workflow enforces multi-database search, quality appraisal using PRISMA, and citation verification for reproducible documentation.

What is the PRISMA protocol for meta-analysis data extraction?

PRISMA is a standardized reporting protocol for systematic reviews and meta-analyses that ensures transparent screening, data extraction, and synthesis. It provides predefined templates to structure scoping, decision logs, and quality assessment for auditable review outputs.

Can I use AMSTAR 2 for quality appraisal in biomedical systematic reviews?

Yes, AMSTAR 2 is applied during the quality appraisal phase of biomedical systematic reviews to assess methodological quality. It works alongside structured planning templates to evaluate studies and generate reproducible documentation in markdown and PDF formats.

How do I verify citations and format bibliographies for a systematic review?

Citation verification in a systematic review checks bibliographic accuracy against source databases and applies standardized formatting. This workflow automates verification after data extraction and synthesis to ensure accurate markdown and export-ready PDF outputs.

Do I need the requests library to orchestrate multi-database literature searches?

Yes, the requests library is required to orchestrate multi-database searches across PubMed, bioRxiv, medRxiv, arXiv, and Semantic Scholar. It handles querying these sources and documenting search strings, dates, and results for reproducible reviews.

What's the best way to organize literature review outputs for reproducible research?

Organize literature review outputs using standardized markdown templates and export-ready PDF formats with reproducible documentation. Copy the review template, rename it to your topic, and follow the multi-phase workflow to generate auditable, citation-verified synthesis files.