literature-research

Search PubMed and compile structured evidence reviews from scholarly sources.

1|Updated Apr 10, 2026
One-click install
npx skills add https://github.com/ezjonline/ezj-automations --skill literature-research-ezjonline
Or copy as Structured Prompt for Agent
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.