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Optimize content for AI-generated answers in ChatGPT, Perplexity, and Google AI Overviews.
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| name | geo |
| description | Optimize content for AI-generated answers in ChatGPT, Perplexity, and Google AI Overviews. |
Optimize web content so it gets cited, quoted, and surfaced by AI engines (ChatGPT, Google AI Overviews/SGE, Perplexity, Bing Copilot, Claude, and others). GEO differs from traditional SEO because AI engines don't rank pages — they synthesize answers from sources. The goal is to become one of those sources.
User asks to optimize content for AI search or AI engines
User wants to audit or rewrite existing pages/posts for GEO readiness
User wants to create new content designed to appear in AI-generated answers
User wants a GEO content strategy or roadmap for their brand/blog
User mentions GEO, generative engine optimization, or AI visibility
User asks how to get cited by ChatGPT, Perplexity, Google AI Overviews, etc.
Key research finding (Princeton/IIT Delhi, KDD 2024): The most impactful GEO signals are statistics (+33.9% visibility), expert quotes (+32%), fluent writing (+30%), and authoritative citations (+30.3%). These numbers should guide prioritization — when time is limited, adding statistics and expert quotes yields the highest return.
AI engines decide what to cite based on several signals. Every recommendation in this skill traces back to one of them:
Direct answerability — Content that directly answers a question in a clear, self-contained way is more likely to be extracted. AI engines prefer content that doesn't require inference to understand.
Authority signals — Cited statistics, named sources, references to studies, and expert attribution increase trust. AI engines weight sourced claims higher than unsourced opinions.
Structured clarity — Well-organized content with clear headings, lists, and logical flow is easier for models to parse and quote. 74% of AI citations come from structured lists and comparison formats.
Topical depth — Content that covers a topic comprehensively with specifics (numbers, examples, comparisons) is preferred over shallow overviews.
Freshness and accuracy — Up-to-date content with current data points wins over stale pages. Contradicting widely-known facts gets filtered out.
Technical accessibility — Proper schema markup, fast load times, and clean HTML help crawlers index content correctly.
Community signals — Reddit, LinkedIn, Quora, and forum mentions are crawled by AI engines. Content that generates authentic discussion in these communities gets additional visibility.
When the user provides existing content (URL, blog post, article, page) to evaluate or improve.
Collect the content — Get the URL or raw content from the user. If it's a URL, fetch and extract the main content body.
Identify the core query — What search or AI prompt is this content answering? What would someone type into ChatGPT to find this?
Evaluate against the GEO scorecard (see scorecard.md for the full checklist).
Apply the rewrite checklist if the user wants improvements (not just an audit):
Add a direct answer block in the first 40-60 words — open with the key phrase ("X is..." or "The best Y for Z is..."). This is the single highest-impact change.
Inject statistics — at least one concrete data point per major section. Flag where data is needed if none is available.
Add or strengthen named expert quotes — direct attribution to a real person or study.
Add source citations inline — link to research, .gov, .edu, or recognized publications.
Rewrite H2/H3 headings as questions or clear topical answers ("How does X work?" not "Overview").
Add or expand a FAQ section — 5-10 questions in real user language at the end.
Improve information density — named entities, stats, and specific claims per paragraph (not vague generalities).
Clearly name the brand/author early in the post and in the byline.
Trim marketing fluff — remove filler phrases that add length without adding facts ("In today's fast-paced world...", "It's important to note...").
Add Article JSON-LD schema (see technical-checklist.md) if the user manages their own site.
# GEO Audit Report: [Page Title or URL]
## Overall GEO Readiness: [Score]/100
## Summary
[2-3 sentence overview of the page's GEO strengths and weaknesses]
## Scores by Category
| Category | Score | Status |
|----------|-------|--------|
| Direct Answerability | X/20 | [needs work / good / strong] |
| Authority & Citations | X/20 | [needs work / good / strong] |
| Structure & Formatting | X/20 | [needs work / good / strong] |
| Topical Depth | X/20 | [needs work / good / strong] |
| Technical Optimization | X/20 | [needs work / good / strong] |
## Detailed Findings
### Direct Answerability
[What's working, what's missing, specific examples from the content]
### Authority & Citations
[Assessment of sourcing, statistics, expert quotes, credibility signals]
### Structure & Formatting
[Heading hierarchy, use of lists, paragraph length, scanability]
### Topical Depth
[Coverage completeness, specificity, comparisons, examples provided]
### Technical Optimization
[Schema markup, meta data, page speed considerations, HTML cleanliness]
## Priority Recommendations
1. [Highest-impact change with specific instructions]
2. [Second priority]
3. [Third priority]
...
## Rewritten Sections (if requested)
[Full rewritten content, followed by a "GEO changes made" summary]
After writing the audit report as a markdown file, convert it to PDF and present it to the user.
.md file (e.g., .local/geo-audit-[site-name].md).pdfkit).When the user wants to write new content from scratch.
Target query / topic — What question is this content answering?
Target audience — Who is reading this?
Content type — Blog post, product page, FAQ, documentation, landing page, comparison page?
Brand voice/tone — Formal, conversational, technical?
Approximate length — Default: 1,200-2,000 words for blog posts/articles.
[TITLE — phrased as a question or definitive answer]
e.g. "What Is X? The Complete Guide" or "How to Do Y in 2026"
[BYLINE — Author name + credentials/title]
[DATE — always include publish date]
[DIRECT ANSWER BLOCK — 40-60 words]
Immediately answers the post's core question. No preamble.
Starts with the key phrase: "X is..." or "The best way to Y is..."
[KEY STATISTICS — 2-3 bullet data points]
Fast-load authority signals AI engines extract immediately.
[H2: Why Does X Matter? / What Is X?]
Dense, factual prose. Named sources. Specific claims.
[H2: How Does X Work? — or next logical question]
Same pattern. Include at least one expert quote or study citation.
[H2: Ranked List or Comparison Table]
"Top 5 ways to..." or "X vs Y" — structured lists are highly citable.
[H2: Common Questions About X]
5-10 FAQ entries in real user language.
Q: [exact phrasing someone would type into ChatGPT]
A: [self-contained 2-3 sentence answer — extractable on its own]
[SOURCES / REFERENCES]
Numbered list of all cited sources with URLs.
For other content types (product pages, documentation, landing pages, comparison pages), read content-patterns.md for type-specific templates.
Research the query landscape — Identify the questions users and AI engines ask about this topic. Think about what an AI engine would need to construct a complete answer.
Plan the content structure — Use the blog post template above or the appropriate pattern from content-patterns.md.
Write with GEO principles applied throughout (see Writing Rules below).
Add technical optimization — Schema markup recommendations, meta descriptions, etc.
When the user wants a strategic GEO roadmap for their blog, brand, or website.
What is the brand/person/product being optimized?
What are the 3-5 core topics they want to be cited for?
Who are the target audiences?
Generate 15-25 specific prompts the target audience would type into ChatGPT, Perplexity, or Google AI Overviews — these are the GEO equivalent of keywords. Focus on:
Informational: "What is the best [topic] for [use case]?"
How-to: "How do I [task related to the niche]?"
Comparative: "X vs Y: which is better for Z?"
Definitional: "What is [core concept]?"
For each target prompt, assess:
Does existing content answer it directly?
What content format would AI engines prefer? (FAQ, article, comparison, listicle)
What authority signals are missing?
Produce a prioritized list of content pieces to create or optimize, ranked by:
Citation potential — How likely is an AI engine to pull from this format?
Competitive gap — Is this topic underserved by competitors?
Business impact — Does citation here drive leads, revenue, or brand awareness?
Read platform-notes.md for engine-specific recommendations.
Recommend the user track:
Mention rate — % of target prompts that return the brand name (test manually or via tools like Profound, Otterly.ai)
Citation rate — % that include a clickable URL to their domain
Citation position — First mention vs. buried in the response
Review cadence — Monthly minimum; weekly for active campaigns
These apply across all modes — as requirements when creating, as recommendations when auditing:
Place the direct answer in the first 40-60 words of the relevant section. AI engines extract opening statements more frequently than buried conclusions. Don't build up to the answer — lead with it, then support it. This is the single highest-impact optimization.
Write sentences that work as standalone quotes. AI engines pull individual sentences or short paragraphs. Each key claim should be a self-contained, factual statement that makes sense without surrounding context.
Every claim gets a source. Include specific numbers, percentages, study names, expert names, and publication references. Unsourced claims are treated as opinions by AI engines. Even when writing original analysis, anchor claims to verifiable data points. Flag where data is needed if it's unavailable — don't leave unsourced assertions.
Definition blocks — "X is [clear definition]" format for definitional queries
Step-by-step lists — Numbered steps for how-to queries
Comparison tables — Side-by-side comparisons for "vs" or "best" queries
FAQ sections — Question-and-answer pairs using actual user questions
Pros/cons lists — For evaluation queries
Each H2/H3 should mirror a natural question someone would ask. AI engines use headings to locate relevant sections. "How Much Does X Cost?" is better than "Pricing Information" because it matches the query pattern.
Cover the topic from multiple angles. AI engines prefer sources that address the full scope of a query — including related questions, edge cases, and common follow-ups. Thin content that only partially answers a question gets passed over for more complete sources.
Include dates, version numbers, "as of [year]" references, and "updated on" indicators. AI engines prefer current information and will note when content appears outdated. Especially critical for Perplexity (real-time crawling) and Google AI Overviews.
Name things explicitly. Instead of "the platform" or "the tool," use the actual name every time. AI engines match entities by name — pronouns and vague references break that matching. The brand/author/company should be unambiguously named and described.
Trim phrases that add length without adding facts. Remove: "In today's fast-paced world...", "It's important to note...", "As we all know...", "When it comes to...". Every sentence should contain a fact, a specific claim, or a direct answer.
Keep paragraphs to 3-5 sentences maximum. Dense walls of text get skipped by both AI engines and human readers.
GEO and SEO compound. Content that ranks well on Google is more likely to be in AI training data. Optimize for both.
Community signals count. Reddit, LinkedIn, Quora, and forum mentions are crawled by AI engines. Encourage authentic discussion around your content.
Write for humans first. AI clarity follows from human clarity — if it reads well to a person, it parses well for an AI engine.
Read content-patterns.md for detailed templates and examples for each content type:
Blog posts and articles
Product and service pages
FAQ and knowledge base pages
Technical documentation
Landing pages
Comparison and review pages
Read technical-checklist.md for:
Schema markup (JSON-LD) recommendations by content type
Meta description optimization for AI extraction
HTML semantics best practices
Page performance considerations
Sitemap and crawlability
Different AI engines have different behaviors. Read platform-notes.md for engine-specific guidance:
ChatGPT/OpenAI — Browsing plugin and training data considerations
Google AI Overviews — Integration with traditional search signals
Perplexity — Real-time crawling and citation patterns
Bing Copilot — Bing index reliance and citation style
Keyword stuffing — AI engines parse semantics, not keyword density. Unnatural repetition hurts readability without improving AI visibility.
Thin content — Short pages that only scratch the surface lose to comprehensive competitors. Depth wins.
Missing attribution — Claims without sources are treated as opinions. Always cite.
Poor structure — Wall-of-text content is hard for AI to parse and quote. Use headings, lists, and short paragraphs.
Ignoring related queries — Answering only the primary question misses opportunities. Cover the "People Also Ask" and follow-up questions.
Outdated information — AI engines deprioritize stale content. Keep data points and references current.
Burying the answer — Leading with background or preamble instead of the direct answer. The answer belongs in the first 40-60 words.
Vague language — Generic statements ("many experts agree", "studies show") without naming the experts or studies. AI engines can't cite what isn't specific.