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content-geo

Optimize web content for AI search citations with answer-first sections and JSON-LD schema.

3|Updated Mar 14, 2026
Search Tags:#content structure#seo#schema markup#e-e-a-t#ai citations#generative engine optimization#answer-first
One-click install
npx skills add https://github.com/Muvon/octomind-tap --skill content-geo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: content-geo
Source: https://github.com/Muvon/octomind-tap/tree/main/skills/content-geo
Command: npx skills add https://github.com/Muvon/octomind-tap --skill content-geo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you structure and optimize web content so AI search engines are more likely to cite your pages in generative answers, not just rank them in traditional search results.

Core Features & Use Cases

  • Answer-first GEO/AEO Structure: Write direct, extractable sections (snippet blocks and self-contained passages) so citations can be pulled from the first part of each section.
  • Experience-Driven Content Signals: Add real-world experience signals (case studies, screenshots, author credentials, and quotes) to avoid generic, AI-derivable filler.
  • Schema & Crawler Readiness: Use JSON-LD schema (especially FAQ/Article/HowTo/Organization/Person/Review where applicable) and align crawl accessibility to improve indexed retrieval and entity recognition.
  • Information Gain & Semantic Completeness: Ensure every section adds novel value versus top results and covers the semantic neighborhood that query fan-out needs.

Quick Start

Use the content-geo Skill to rewrite a target article into an answer-first, citation-optimized draft that includes extractable 40–50 word H2 answers, 134–167 word standalone passages, FAQ content, relevant JSON-LD, and experience-backed sections.

Frequently Asked Questions about content-geo

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

FAQPage Schema
How do I optimize content for AI search engines to get cited in generative answers?▼

Generative engine optimization (GEO) structures web content with answer-first sections, self-contained passages, and JSON-LD schema so AI search engines can extract, ground, and cite your page inside generative answers instead of ignoring it.

What is the best way to structure an article for AI Overviews and ChatGPT citations?▼

The best way to structure articles for AI citations is using answer-first formatting: 40–50 word direct H2 answers and 134–167 word standalone passages that act as extractable snippet units for AI retrieval systems.

Does schema markup help with generative engine optimization and AI search retrieval?▼

Yes, schema markup helps with generative engine optimization by aligning crawl accessibility and using JSON-LD formats like FAQ, Article, and HowTo to improve indexed retrieval and entity recognition for AI grounding.

How do I add E-E-A-T experience signals to my content for AI search engines?▼

You add E-E-A-T experience signals by integrating real-world proof into your content, such as case studies, screenshots, author credentials, and direct quotes, which replaces generic AI-derivable filler and strengthens citation likelihood.

Why does my web content get ignored by Perplexity and Google AI Overviews?▼

Your web content gets ignored by AI search engines when it lacks information gain, missing semantic coverage for query fan-out, or fails to provide extractable answer-first sections that generative engines need for retrieval and grounding.

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