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literature-review

Search academic databases, verify citations, and generate markdown and PDF documents.

Updated May 8, 2026
Search Tags:#data extraction#citations#systematic review#literature review#academic research
One-click install
npx skills add https://github.com/Zeyuyang-0420/bio-ai-research-skills --skill literature-review-zeyuyang-0420
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: literature-review
Source: https://github.com/Zeyuyang-0420/bio-ai-research-skills/tree/main/categories/scientific-communication/literature-review
Command: npx skills add https://github.com/Zeyuyang-0420/bio-ai-research-skills --skill literature-review-zeyuyang-0420

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires parallel-web, gget, bioservices, datacommons-client, pydeseq2, scanpy, anndata, biopython, matplotlib, seaborn, brand-guidelines, internal-comms, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the process of conducting literature reviews, saving time and reducing the risk of human error in the search, selection, and analysis of scientific literature.

Core Features & Use Cases

  • Multi-Database Search: Search across multiple academic databases with a single command.
  • Citation Verification: Automatically verify all citations for accuracy.
  • Document Generation: Generate professional markdown and PDF documents with formatted citations.
  • Use Case: If you need to write a literature review for a research paper or thesis, this Skill can help you efficiently search for relevant articles, extract key information, and format the final document.

Quick Start

To use the literature-review skill, follow these steps:

  1. Run the command: parallel-cli search "your research topic" to search across academic databases.
  2. Review the search results and select the articles you want to include in your review.
  3. Use the scripts/search_databases.py script to aggregate and process the selected articles.
  4. Use the scripts/verify_citations.py script to verify the accuracy of all citations.
  5. Generate the final markdown and PDF document using the scripts/generate_pdf.py script.

Frequently Asked Questions about literature-review

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

FAQPage Schema
How do I automate a systematic review across multiple academic databases?▼

Automating a systematic review requires searching across multiple academic databases, selecting articles, verifying citations, and generating formatted documents. This process uses Python libraries and scripts to execute multi-database searches and aggregate the results.

How can I verify citations for accuracy during a literature review?▼

Verifying citations for accuracy involves executing a dedicated Python script to cross-check extracted references against source databases. This automated citation verification step reduces human error and ensures all formatted documents contain validated reference data.

Does this literature review process support generating PDF and markdown documents?▼

Generating PDF and markdown documents is fully supported through dedicated Python scripts. The document generation process takes the processed articles and verified citations, outputting professional formatted files suitable for academic research papers or theses.

Can I use Python libraries like biopython and scanpy for academic research text processing?▼

Using Python libraries like biopython and scanpy for academic research text processing is supported within this workflow. These dependencies, alongside datacommons-client and parallel-web, enable comprehensive data extraction, web search, and scientific literature analysis.

What is the best way to extract key information from scientific literature for a research paper?▼

Extracting key information from scientific literature is best achieved by aggregating selected articles through a specific Python script. This text processing step isolates relevant data from multiple academic databases, preparing the content for final review document generation.

What are the limitations of using automated scripts for a comprehensive literature search?▼

Limitations of automated comprehensive literature searches include the prerequisite of running specific search commands and relying on multiple scientific dependencies. Users must manually review aggregated search results to select articles, ensuring the final document meets specific academic research criteria.

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