Bencium Aeo

bencium/bencium-marketplace/bencium-aeo/skills/bencium-aeo

作者 bencium5de46a39b464無授權條款445 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫4 天前更新

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 產生的概覽

產生答案引擎優化內容與結構化資料,提高頁面被 AI 搜尋引擎引用的機會。

功能
這項技能為 AI 搜尋能見度產生 AEO 優化內容,包括簡短的產品概述、15 則常見問題與 FAQPage JSON-LD 結構化資料、證據面板,以及 HowTo、Product、Organization 等其他結構化標記。它也提供評估框架,從可擷取性、主題聚焦、權威性與時效性四個面向為現有內容評分,並附上實作檢查清單與橫跨 ChatGPT、Claude、Gemini 的測試流程。它明確不適用於傳統 SEO。
適用情境
當目標是在 AI 答案引擎中取得能見度而非傳統搜尋排名時使用,例如為 AI 引用優化頁面、建立 FAQ 結構化資料或證據面板,或評估內容是否便於 LLM 擷取。也適用於提到 ChatGPT、Claude、Gemini、AI Overviews 或 GEO 的需求。
執行需求
不隨附指令碼,僅為說明性內容。它依賴隨附的參考文件 prd.md 與 story-structured.md 取得完整範本與指引,測試流程則假定可存取 ChatGPT、Claude、Gemini 等 AI 助理。

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

來源與署名

來源:bencium/bencium-marketplace位於bencium-aeo/skills/bencium-aeo提交5de46a3

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