geo-fundamentals

Structure content with JSON-LD, author attribution, and FAQs to improve AI citations.

Updated Aug 30, 2024
One-click install
npx skills add https://github.com/jfrometa/esquizo --skill geo-fundamentals-jfrometa
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: geo-fundamentals
Source: https://github.com/jfrometa/esquizo/tree/main/.agent/skills/geo-fundamentals
Command: npx skills add https://github.com/jfrometa/esquizo --skill geo-fundamentals-jfrometa

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

GEO Fundamentals addresses the challenge of getting AI engines to reliably cite high-quality sources by aligning content with best practices for Generative Engine Optimization.

Core Features & Use Cases

  • Structured data guidance (JSON-LD, schema.org entities) to improve AI extraction and citability.
  • Clear author attribution, publication dates, and FAQ sections to support E-E-A-T signals.
  • Content-quality checks and scaffolding for AI-ready citability across websites, knowledge bases, and product docs.
  • Use Case: Content teams preparing blog posts, knowledge bases, and product documentation to maximize AI citations.

Quick Start

To begin, run the GEO Fundamentals audit on your project to identify missing structured data, author information, and dates, then implement the recommended schema, headings, and FAQ sections to improve AI citations.

Frequently Asked Questions about geo-fundamentals

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

FAQPage Schema
How do I optimize my content for AI citations and generative engine retrieval?

To optimize content for AI citations, you must align your pages with generative engine optimization practices by adding structured data like JSON-LD, clear headings, author attribution, and publication dates so AI crawlers can easily extract and cite your sources.

What structured data formats improve AI extraction and citability?

JSON-LD and schema.org entities are the primary structured data formats that improve AI extraction and citability. They provide machine-readable metadata that helps generative engines parse your content accurately and attribute it as a reliable source.

How do I audit my website for AI-ready content and missing metadata?

You can audit your website for AI-ready content by running an analysis script to identify missing structured data, absent author attribution, and omitted publication dates, then implementing the recommended schema and FAQ sections to maximize AI citations.

Does adding FAQ sections and author attribution help secure AI-generated citations?

Yes, adding FAQ sections and author attribution directly supports E-E-A-T signals and secure AI-generated citations. Clear evidence-backed data and explicit authorship allow AI retrieval systems to verify source credibility and extract relevant responses.

Can I use generative engine optimization for product documentation and knowledge bases?

Yes, generative engine optimization applies to product documentation and knowledge bases. By structuring your technical docs with clear headings, JSON-LD metadata, and publication dates, you ensure high visibility and reliable extraction in AI-generated responses.

What is the best way to structure web pages for generative engine crawlers?

The best way to structure web pages for generative engine crawlers is to implement schema.org entities, use clear hierarchical headings, provide evidence-backed data, and include explicit JSON-LD metadata to maximize content extraction and AI citation frequency.