Bencium Aeo

If you're trying to get your content cited by ChatGPT, Claude, or Google's AI Overviews, this is the playbook. It's built around the 18-token extraction rule (LLMs quote ~15-20 word self-contained sentences) and generates FAQ schemas, evidence panels with citations, and single-topic focused pages instead of SEO listicles. The Princeton-backed approach is authority-aware: challenger sites need aggressive optimization with 5-7 extraction points per page, while top-ranked sites should go light to avoid the 30% visibility drop from over-optimization. Includes JSON-LD templates, freshness protocols, and testing prompts for all major AI engines. This is for AI citation visibility, not traditional search rankings.

skills.sh installs: 3.5K
GitHub stars: 491
last updated: Aug 21, 2026

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Install

$ npx -y skills add bencium/bencium-marketplace --skill bencium-aeo --agent claude-code

Installs into .claude/skills of the current project.

Files

AEO Content Optimization Skill

Answer Engine Optimization - Optimize content for AI citations, not traditional search rankings.

When to Use This Skill

Use this skill when:

User asks to optimize content for AI search/citations
User mentions ChatGPT, Claude, Gemini visibility
User wants FAQ schema, JSON-LD, or structured data for AI
User asks about GEO (Generative Engine Optimization)
User wants to analyze content for AI extraction readiness
User mentions "AI Overviews" or "answer engines"

NOT for traditional SEO - This is specifically for AI/LLM citation optimization.

Core Reference

Full templates and guidelines: Read prd.md in this directory for complete implementation details.

Quick Reference: Key Principles

The 18-Token Extraction Rule

LLMs extract self-contained sentences of ~18 tokens (~15-20 words). Key claims must be complete, quotable statements requiring zero surrounding context.

Good: "Eight-API synthesis reduces property analysis errors by 67%." (9 tokens) Bad: "Our system is incredibly fast and delivers amazing results." (vague)

SKILL.md on GitHub