literature-research

Search PubMed and compile structured evidence reviews from scholarly sources.

1|Updated Apr 10, 2026

Search Tags:#literature review #academic research #clinical trials #pubmed #evidence synthesis #unpaywall #full-text retrieval

Ready to run

npx skills add https://github.com/ezjonline/ezj-automations --skill literature-research-ezjonline

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: literature-research
Source: https://github.com/ezjonline/ezj-automations/tree/main/skills/literature-research
Command: npx skills add https://github.com/ezjonline/ezj-automations --skill literature-research-ezjonline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, python-dotenv, and includes scripts (resource) components.

What problem does it solve?

This Skill removes the manual effort of searching academic databases, collecting paper metadata, and turning scattered findings into a coherent literature review.

Core Features & Use Cases

PubMed Search: Query scholarly literature and retrieve structured article metadata for screening and analysis.
Deep Review Pipeline: Enrich results with full-text availability, clinical trial matching, and outcome extraction for evidence synthesis.
Use Case: A researcher studying menopause treatments can gather studies, identify relevant trials, compare interventions, and compile a review-ready summary in one workflow.

Quick Start

Ask the literature-research skill to search PubMed for your topic and produce a deep review from the results.

Frequently Asked Questions about literature-research

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

FAQPage Schema

How do I search PubMed and compile a literature review automatically?▼

To search PubMed and compile a literature review, query your topic to retrieve structured article metadata, screen papers, and synthesize findings into a review-ready dataset. The workflow supports evidence synthesis and structured comparison of interventions or outcomes.

How does Unpaywall lookup work for finding full-text articles?▼

Unpaywall lookup works by querying open access APIs to determine full-text availability for articles found during your literature search. It enriches PubMed metadata by identifying accessible PMC full-text articles for evidence synthesis.

What is the best way to match clinical trials to academic literature?▼

The best way to match clinical trials to academic literature is using a deep review pipeline that enriches PubMed search results with trial matching and outcome extraction. This structured comparison compiles interventions and outcomes into review-ready summaries.

Do I need Python and dotenv configured to retrieve PMC full-text articles?▼

Yes, you need Python with dotenv configured to retrieve PMC full-text articles. The workflow requires Python-based HTTP requests and dotenv-managed API configuration to parse XML and return article metadata and full-text availability.

Can I extract and compare interventions from scholarly sources for evidence synthesis?▼

Yes, you can extract and compare interventions from scholarly sources for evidence synthesis. The deep review pipeline analyzes PubMed and PMC full-text retrieval results to produce structured comparisons of interventions and outcomes.