Bencium Aeo

by bencium5de46a39b464No license445 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 4 days ago

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.

AI-generated overview

Generates Answer Engine Optimization content and schema so pages are more likely to be cited by AI search engines.

What it does
This skill produces AEO-optimized content for AI search visibility, including a short product overview, 15 FAQs with FAQPage JSON-LD schema, evidence panels, and other structured data such as HowTo, Product, and Organization markup. It also provides an assessment framework that scores existing content on extraction, focus, authority, and freshness, plus an implementation checklist and a testing protocol across ChatGPT, Claude, and Gemini. It is explicitly not for traditional SEO.
When to use it
Use it when the goal is visibility in AI answer engines rather than classic search rankings, such as optimizing pages for AI citations, creating FAQ schemas or evidence panels, or auditing content for LLM extraction readiness. It also fits requests mentioning ChatGPT, Claude, Gemini, AI Overviews, or GEO.
Requirements
No scripts are shipped; it is instructions only. It relies on the bundled reference documents prd.md and story-structured.md for full templates and guidelines, and the testing protocol assumes access to AI assistants such as ChatGPT, Claude, and Gemini.

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 LevelOptimization 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 datePublished and dateModified
  • 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):

DimensionWhat to Check
ExtractionHow many citation-ready sentences under 18 tokens?
FocusSingle topic or sprawling multi-topic?
AuthorityExpert attribution with credentials? Citations?
FreshnessUpdated 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:

  1. Recognition: "What is [Product]?" (ChatGPT, Claude, Gemini)
  2. Comparison: "Compare [Product] to [Competitor]"
  3. Best for: "What's the best [category] for [use case]?"
  4. 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 templates
  • story-structured.md - Framework summary from Princeton study

Source and attribution

Source:bencium/bencium-marketplaceinbencium-aeo/skills/bencium-aeoat commit5de46a3

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

Report or request removal

More from bencium/bencium-marketplace

Insurgent Campaign

bencium

Grassroots-first campaign design for anyone being outspent — startups vs. incumbents, NGOs vs. corporate comms, movements vs. state-backed machines, solo brands vs. big-budget competitors. Ideates awareness, launch, fundraising, mobilization, community-build, counter-narrative, referral, founder-story, and coalition campaigns. Triggers on "campaign plan", "marketing strategy", "ad budget", "should I advertise", "paid vs organic", "launch plan", "grassroots", "low budget marketing", "NGO campaign", "outspent", "competitor has bigger budget", "how do I compete without money". Also trigger on any spend asymmetry, collapsing organic reach, rising CPAs, or a trust/credibility problem — even without the word "campaign". Nudge activation when the user debates buying ads, boosting posts, or hiring influencers; they are likely about to burn money on a channel that will not persuade.

Awaiting classification445updated 4 days ago

Vanity Engineering Review

bencium

Reviews code, architecture, PRs and technical plans for vanity engineering and produces a scored assessment with kill criteria.

Software Development445updated 4 days ago

Renaissance Architecture

bencium

Guides software architecture and UI/UX decisions toward first-principles, simplicity-first design rather than derivative work.

Software Development445updated 4 days ago

Negentropy Lens

bencium

A decision-support framework for evaluating systems, architectures and strategies through entropy versus negentropy, surfacing tacit knowledge gaps.

Research & Analysis445updated 4 days ago

Human Architect Mindset

bencium

Guides systematic software architecture thinking: domain modeling, systems analysis, constraints, and AI-aware decomposition.

Software Development445updated 4 days ago

Hungarian Humanizer

bencium

Detects and rewrites AI-sounding markers in Hungarian text so it reads like a native speaker wrote it.

Writing & Content445updated 4 days ago
Bencium Aeo Agent Skill | SourceWeft