bencium-aeo
bencium/bencium-marketplace
Optimize content for AI citations and answer engine visibility across ChatGPT, Claude, Gemini, and AI Overviews.
What is bencium-aeo?
Generate AEO (Answer Engine Optimization) content designed for AI search visibility and LLM citation rather than traditional SEO. Use this skill when optimizing websites for AI citations, creating FAQ schemas, evidence panels, or analyzing content for AI extraction readiness.
- Generate 50-word product overviews with freshness dates
- Create 15 FAQs with 30-50 word answers and FAQPage JSON-LD schema
- Build evidence panels with methodology, data sources, dates, and limitations
- Apply the 18-token extraction rule to ensure LLM-quotable sentences
- Score content readiness across extraction, focus, authority, and freshness dimensions
- Identify anti-patterns like keyword stuffing and vague hedged language that harm AI visibility
How to install bencium-aeo
npx skills add https://github.com/bencium/bencium-marketplace --skill bencium-aeoHow to use bencium-aeo
- 1.Identify your site's authority level (Challenger, Established, or Rank-5+) to determine optimization intensity
- 2.Generate or audit a product overview (50 words) with dated freshness signals
- 3.Create 15 FAQs with natural 7-12 word questions and 30-50 word answers
- 4.Add FAQPage JSON-LD schema with datePublished and dateModified to page head
- 5.Build evidence panels for major claims including methodology, data source, collection date, and limitations
- 6.Test content recognition with ChatGPT, Claude, and Gemini using comparison and how-to queries
- 7.Validate schema markup with Google Rich Results Test and track mention accuracy
Use cases
- Optimize product pages for ChatGPT and Claude citations by structuring claims with supporting data and expert attribution
- Create FAQ schemas for websites to increase visibility in AI-generated overviews and answer engines
- Analyze existing content for AI extraction readiness and identify gaps in citation-ready statements
- Develop single-topic focused pages that outperform multi-topic guides in AI search results
- Implement freshness signals and dated evidence panels to maintain AI citation visibility over time
- Content strategists optimizing for AI search and answer engines
- Product marketing teams building AI-visible product pages
- Technical writers creating documentation for LLM extraction
- SEO professionals transitioning to answer engine optimization
- Website owners competing for AI citations in ChatGPT, Gemini, and Claude
bencium-aeo FAQ
AEO optimizes for AI citations and LLM extraction, not keyword rankings. It focuses on citation-ready sentences under 18 tokens, dated evidence, and expert attribution rather than keyword density and backlinks.
LLMs extract self-contained sentences of approximately 18 tokens (~15-20 words). Key claims must be complete, quotable statements requiring zero surrounding context to be cited by AI systems.
95% of AI citations come from content updated within the last 10 months. Static content loses visibility quickly, so implement weekly micro-updates and refresh major claims regularly.
No. Established, high-authority sites that over-optimize lose 30% visibility. Use light-touch optimization (1-2 strategic points) instead of aggressive tactics designed for challenger sites.
FAQPage JSON-LD is most important, followed by HowTo, Product, and Organization schemas. All must include datePublished and dateModified fields for freshness signals.
Full instructions (SKILL.md)
Source of truth, from bencium/bencium-marketplace.
name: bencium-aeo description: Generate AEO-optimized content (Answer Engine Optimization) for AI search visibility - ChatGPT, Claude, Gemini, AI Overviews. Use when optimizing websites for AI citations, creating FAQ schemas, evidence panels, or analyzing content for LLM extraction readiness.
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)
Single-Topic Focus Pages
Single-concept pages vastly outperform multi-topic content. Create focused URLs like domain.com/specific-concept rather than comprehensive guides.
Citations + Statistics = 30-40% More Visibility
Every major claim needs:
- Verifiable data with methodology
- Date of data collection
- Expert attribution (Name + Credentials + Org)
Freshness is Critical
95% of AI citations come from content updated in last 10 months. Static content dies.
Authority Level Determines Strategy
| Authority Level | Optimization Approach |
|---|---|
| Challenger (new sites, low authority) | Aggressive: 5-7 extraction points per page, heavy citations, weekly micro-updates |
| Established (top-ranked, well-known) | Light touch: 1-2 strategic points, trust existing credibility, avoid over-optimization |
Princeton finding: Rank-5 sites gained 115% visibility with aggressive optimization. Rank-1 sites that over-optimized lost 30%.
What to Generate
When user requests AEO content, generate:
1. Product Overview (50 words)
- What it is (one clause)
- Scope/timeframe context
- Why it matters (value proposition)
- "Last updated" date
2. 15 FAQs with Schema
- Questions: 7-12 words, natural language
- Answers: 30-50 words (sweet spot for AI extraction)
- FAQPage JSON-LD schema with
datePublishedanddateModified - Persistent anchor IDs (#faq-slug)
3. Evidence Panels
For every important claim:
- Claim statement
- Methodology
- Data source + URL
- Date of data collection
- Limitations
- Contact for questions
4. JSON-LD Schema
- FAQPage (most important)
- HowTo (for guides)
- Product (for product pages)
- Organization (for About page)
Anti-Patterns (What to Avoid)
Traditional SEO Tactics Harm GEO
- Keyword stuffing
- Generic listicles without original insight
- Vague hedged language ("may help", "could potentially")
- Multi-topic comprehensive guides
- Over-optimization on established sites
Content Structure Errors
- FAQ answers over 50 words
- Buried answers (put conclusion first)
- Pronoun ambiguity ("it" instead of "the product")
- Missing dates and freshness signals
- No schema markup
Assessment Framework
When analyzing content for AEO readiness, score (0-10):
| Dimension | What to Check |
|---|---|
| Extraction | How many citation-ready sentences under 18 tokens? |
| Focus | Single topic or sprawling multi-topic? |
| Authority | Expert attribution with credentials? Citations? |
| Freshness | Updated within 90 days? Dated content? |
Quick test: Can you copy-paste 3 sentences that fully answer a question without context?
Implementation Checklist
- Product overview: 50 words, dated, under H1
- 15 FAQs: 30-50 words each, natural questions
- Evidence panels: method, data, date, limitations
- "Last updated" dates on every section
- FAQPage JSON-LD schema in
<head> - Persistent anchor IDs for FAQs
- Validated with Google Rich Results Test
Testing Protocol
After implementation, test with:
- Recognition: "What is [Product]?" (ChatGPT, Claude, Gemini)
- Comparison: "Compare [Product] to [Competitor]"
- Best for: "What's the best [category] for [use case]?"
- How-to: "How do I [task with product]?"
Track: Mentioned? Linked? Accurate? Evidence quoted?
Full Documentation
For complete templates, examples, and detailed guidelines, read:
prd.md- Full AEO content generation guide with HTML templatesstory-structured.md- Framework summary from Princeton study
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