literature-review

Automate multi-database literature searches and generate reproducible Markdown and PDF outputs.

71|18|Updated Mar 6, 2026
One-click install
npx skills add https://github.com/Science-Discovery/Aether --skill literature-review-science-discovery
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: literature-review
Source: https://github.com/Science-Discovery/Aether/tree/main/.opencode/skills/literature-review
Command: npx skills add https://github.com/Science-Discovery/Aether --skill literature-review-science-discovery

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Automate the coordination, synthesis, and documentation of literature reviews to reduce time and ensure reproducibility across databases and formats.

Core Features & Use Cases

  • Multi-database search orchestration across PubMed, arXiv, bioRxiv, Semantic Scholar, and more
  • Automated citation verification and multi-style formatting
  • Output generation in Markdown and PDF with PRISMA-compatible reporting
  • Reproducible workflows and audit trails for research synthesis

Quick Start

Tell the AI to generate a structured literature review for a given topic using the configured databases and output formats.

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 literature review across multiple databases?

A PRISMA literature review requires structured reporting of search and selection processes. This Skill generates PRISMA-aligned reporting alongside Markdown and PDF outputs, ensuring your systematic review meets reproducibility and documentation standards.

Can I verify citations and format references in different styles automatically?

Automated citation verification is supported natively by this Skill. It checks extracted sources against databases and applies multi-style formatting to your references, ensuring citation accuracy before generating the final Markdown or PDF document.

What is the best way to generate reproducible Markdown and PDF outputs for research synthesis?

Generating reproducible Markdown and PDF outputs is achieved through automated workflow orchestration. This Skill creates audit trails for your systematic search, deduplication, and extraction steps, ensuring your research synthesis is fully documented and reproducible.

Does this literature review automation work with Semantic Scholar and arXiv?

Yes, literature review automation works with Semantic Scholar and arXiv. The multi-database search orchestration includes these sources alongside PubMed and bioRxiv, allowing you to coordinate comprehensive systematic searches across scientific and biomedical platforms.

Do I need Python requests installed to run multi-database systematic searches?

Yes, the Python requests dependency is required to run multi-database systematic searches. This library handles the API connections to PubMed, arXiv, and Semantic Scholar, enabling the automated retrieval and verification of citations.