Verified:GitHub

systematic-literature-review

Conduct systematic literature reviews following PRISMA 2020 guidelines.

Updated Feb 20, 2026

Search Tags:#data extraction #systematic review #literature review #PRISMA #research methodology #adversarial testing #evidence synthesis

Ready to run

npx skills add https://github.com/yananlong/codex-skills --skill systematic-literature-review-yananlong

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: systematic-literature-review
Source: https://github.com/yananlong/codex-skills/tree/main/skills/systematic-literature-review
Command: npx skills add https://github.com/yananlong/codex-skills --skill systematic-literature-review-yananlong

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex and time-consuming process of conducting systematic literature reviews, ensuring rigorous methodology and comprehensive analysis of research publications.

Core Features & Use Cases

Full PRISMA 2020 Compliance: Follows core PRISMA guidelines for transparent reporting.
Automated Workflow: Manages discovery, deduplication, screening, evidence extraction, synthesis, and confidence grading.
Adversarial Stress-Testing: Red-teams conclusions for robustness and identifies potential biases or overgeneralizations.
Use Case: A researcher needs to synthesize the state-of-the-art in a specific AI domain. This Skill can be used to discover, screen, and synthesize relevant papers, providing a structured and confidence-graded overview of the evidence.

Quick Start

Use the systematic-literature-review skill to conduct a literature review on the topic of "large language models" within the "artificial intelligence" domain.

Frequently Asked Questions about systematic-literature-review

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

FAQPage Schema

How do I automate a systematic literature review following PRISMA 2020 guidelines?▼

Automate a systematic literature review by using a workflow that manages paper discovery, deduplication, screening, data extraction, and evidence synthesis. This ensures full PRISMA 2020 compliance while prioritizing peer-reviewed publications over preprints and resolving version conflicts.

What is adversarial stress-testing in evidence synthesis?▼

Adversarial stress-testing in evidence synthesis red-teams research conclusions to evaluate robustness, identifying potential biases or overgeneralizations. This process ensures confidence grading accurately reflects the reliability of the synthesized literature.

How do I extract data from research papers for a systematic review?▼

Extract data from research papers for a systematic review through an automated workflow that handles screening and evidence extraction. This process synthesizes findings while assigning confidence grades to evaluate the strength of the extracted evidence.

Can I use an automated tool to deduplicate research papers and resolve version conflicts?▼

Yes, you can use an automated workflow to deduplicate research papers and resolve version conflicts. This deduplication process operates during the discovery phase, ensuring a clean dataset for screening and prioritizing peer-reviewed publications over preprints.

How do I conduct a literature review that prioritizes peer-reviewed publications over preprints?▼

Conduct a literature review prioritizing peer-reviewed publications by configuring the automated discovery and screening workflow to filter sources. This methodology resolves version conflicts and assigns confidence grades to synthesize robust evidence.