"Improve visibility in AI search and answer engines (ChatGPT, Perplexity, Gemini, Google AI Overviews) using GEO: crawl controls (robots/WAF/llms.txt), answer-ready content and entity pages, citation strategy, and measurement (query bank, share of model)."
Install
npx skillscat add vasilyu1983/ai-agents-public/marketing-ai-search-optimization Install via the SkillsCat registry.
We need to produce a 2-3 sentence plain-text summary, objective, factual, no marketing language, no superlatives, no calls to action, natural prose, no bullet points, no headings, no markdown. At most 60 words. Must explain what skill does, what problem it solves, when to use. From description: skill is marketing-ai-search-optimization, for optimizing content for AI search engines and answer platforms (ChatGPT, Perplexity, Gemini, Google AI Overviews).
AI Search & Answer Engine Optimization (GEO)
Improve how assistants retrieve, summarize, and cite your pages.
For traditional SEO: Use marketing-seo-complete instead.
GEO vs SEO (Overlap Map)
Use this to prevent “GEO-only” work that ignores discoverability and conversion.
GEO is best at
- Making pages easier for assistants to extract, summarize, and cite
- Building entity/proof structures that improve citation probability
- Measuring assistant visibility via query banks and citation share
SEO is still required for
- Getting pages discovered and indexed reliably (crawlability, internal linking, canonicalization)
- Capturing demand in classic search surfaces (SERPs, video, local, forums)
- Avoiding regressions from technical changes (rendering, performance, duplication)
Default operating rule
- Keep classic SEO and conversion work running; treat GEO as a structured overlay on top of high-intent pages.
GEO Monitoring vs GEO Optimization
This skill covers optimization — improving your content so AI platforms cite you more often.
For monitoring infrastructure — building the systems that track whether AI platforms cite you — see project-aeo-monitoring-tools.
Typical workflow: Monitor (track current visibility) -> Optimize (improve content) -> Measure (verify improvement)
| Activity | This skill | project-aeo-monitoring-tools |
|---|---|---|
| Content structure for citation | Yes | — |
| Entity and proof optimization | Yes | — |
| Query bank construction | Quick guidance | Full methodology |
| API orchestration and pipelines | — | Yes |
| Citation extraction and analysis | — | Yes |
| Share of Model dashboard | Concept | Implementation |
| Bot analytics and crawl tracking | — | Yes |
| Cost estimation and transparency | — | Yes |
Quick start (30–60 min)
- Build a query bank (30–100 queries for quick start; scale to 250–500 for advanced monitoring): problems, comparisons, "best", "vs", integrations, and pricing questions.
- Confirm assistants can fetch content (robots/WAF/SSR): use
assets/audits/crawler-access-audit.md. - Run a baseline visibility audit: use
assets/audits/search-visibility-audit.mdandassets/audits/ai-search-content-audit.md. - Ship one high-leverage page update: use
assets/content/ai-search-content-brief.md+assets/content/answer-focused-article-template.md. - Set up measurement + retest cadence: use
references/measurement-analytics.mdandassets/testing/ai-search-testing-protocol.md.
Core workflow
1) Decide scope (avoid wasted work)
- Confirm discovery channel: check whether your ICP uses assistants for research and comparisons.
- Pick one primary platform first (Google AI Overviews vs ChatGPT vs Perplexity) based on your audience.
- Treat GEO as additive: keep classic SEO and conversion work running.
2) Ensure assistants can access your content
- Allow/deny crawlers explicitly: use
references/ai-crawler-technical-setup.mdandassets/technical/robots-txt-ai-crawlers.md. - Reduce JS dependency for critical copy (SSR/SSG): use
assets/technical/server-side-rendering-guide.md. - Add
llms.txtwhen useful as a navigation map (not a guarantee): useassets/technical/llms-txt-template.md. - Review emerging
.well-known/AI discovery standards (llmprofiles.json,mcp.json,agents.json): useassets/technical/well-known-ai-discovery.md.
3) Make pages easy to extract and cite
- Put a direct, quotable answer block in the first screenful (then expand with proof).
- Use stable entities (product, category, competitors, integrations): use
references/entity-semantic-optimization.md. - Use repeatable content structures for questions, comparisons, and "best for": use
references/content-structure-patterns.md.
Implementation reference: The AEO monitoring platform's recommendation engine (
src/lib/recommendations/engine.ts) automates gap analysis against these patterns. The optimization dashboard (src/app/optimize/page.tsx) surfaces actionable recommendations. Seeproject-aeo-monitoring-toolsfor the full implementation.
- Create/refresh high-intent pages first (alternatives, integrations, pricing, security, implementation): use
assets/strategy/ai-search-growth-plan.md.
4) Build off-site entity presence and earned citations
- Get your brand into third-party sources AI trusts (G2, Reddit, Wikipedia, YouTube, industry listicles): use
references/earned-aeo-third-party-citations.md. - Strengthen Knowledge Graph presence (Wikidata, Google Business Profile,
sameAslinking): see Knowledge Graph section inreferences/entity-semantic-optimization.md. - Create multimodal content (video, transcripts, audio) for AI platforms that cite non-text sources: use
references/multimodal-content-optimization.md. - For e-commerce: implement Google UCP for agentic shopping visibility: use
references/commerce-protocol-ucp.md.
5) Add proof and trust hooks (citation fuel)
- Prefer primary sources and verifiable numbers; attribute claims clearly.
- Show authorship, review, and freshness (
dateModified/ "Last updated") where appropriate. - Avoid "LLM bait": prioritize user value and factual accuracy.
6) Measure, iterate, and defend against regressions
- Track "share of model" / citation share using your query bank, not vanity rankings. For automated tracking, see project-aeo-monitoring-tools (custom infrastructure) or commercial alternatives in
references/llm-tracking-tools.md. - Re-test after shipping changes; keep snapshots of answers and citations.
- Separate SEO wins vs assistant visibility wins; avoid false attribution.
Implementation Examples
Query Bank Construction
Quick start (30-100 queries):
Problems: "how to [solve X]", "why does [Y happen]"
Comparisons: "[product] vs [competitor]", "best [category] for [use case]"
Integrations: "[product] [integration] setup", "does [product] work with [tool]"
Pricing: "[product] pricing", "[product] free plan"Advanced (250-500 queries): Expand with persona variants, regional variations, long-tail variations, and seasonal queries. See project-aeo-monitoring-tools for full query bank methodology.
Content Structure Patterns
Apply these patterns to high-intent pages:
Comparison page:
H1: [Product A] vs [Product B]: [Year] Guide
TL;DR: 2-3 sentence verdict
Table: Feature comparison
Sections: Use cases, pricing, verdict
Alternatives page:
H1: Best [Product] Alternatives in [Year]
TL;DR: Top 3 picks with one-line reasons
Table: Feature + pricing matrix
Sections: Detailed review per alternative
Integration page:
H1: How to Connect [Product] with [Tool]
Steps: Numbered setup guide
Code: Configuration examples
FAQ: Common issuesEntity Optimization
Structure your brand entity for AI recognition:
Brand Kit (maintain centrally):
- Official name and variants
- Category/industry classification
- Key differentiators (3-5 unique claims)
- Proof points (metrics, case studies, awards)
- Integration ecosystem
Apply to every high-intent page:
- Use official name consistently (not abbreviations)
- Reference category explicitly ("CRM platform" not just "tool")
- Include at least one proof point per pageOptimization vs Monitoring Workflow
Step 1: Baseline — Run query bank through AI platforms (project-aeo-monitoring-tools)
Step 2: Audit — Score current content against citation-ready patterns (this skill)
Step 3: Implement — Apply content structure patterns to top-priority pages (this skill)
Step 4: Re-measure — Run query bank again after 2-4 weeks (project-aeo-monitoring-tools)
Step 5: Iterate — Focus on pages with largest gap between potential and actual citationsWhat to load (progressive disclosure)
- Platform notes:
references/platform-google-ai-overviews.md,references/platform-chatgpt.md,references/platform-perplexity.md,references/platform-gemini.md,references/platform-claude.md - Technical access:
references/ai-crawler-technical-setup.md,references/ai-indexing-complete-guide.md,assets/technical/well-known-ai-discovery.md - Off-site & earned AEO:
references/earned-aeo-third-party-citations.md,references/multimodal-content-optimization.md - E-commerce:
references/commerce-protocol-ucp.md - Measurement:
references/measurement-analytics.md,references/llm-tracking-tools.md - Prompt/query mining:
references/prompt-query-optimization.md,references/competitor-citation-gap.md,references/citation-optimization-strategies.md - Primary sources list:
data/sources.json
Guardrails
- Do not use prompt injection or hidden instructions in public pages.
- Do not claim endorsements or fabricate sources, stats, or quotes.
- Treat
robots.txtas policy; enforce access with auth/WAF where needed.
Resources
| Resource | Purpose |
|---|---|
| references/ai-indexing-complete-guide.md | Full DO & DON'T guide |
| assets/technical/well-known-ai-discovery.md | .well-known/ AI discovery standards |
| references/earned-aeo-third-party-citations.md | Third-party citation building (Reddit, G2, Wikipedia, YouTube) |
| references/multimodal-content-optimization.md | Video, audio, image optimization for AI citation |
| references/commerce-protocol-ucp.md | Google UCP & agentic commerce (e-commerce only) |
| references/platform-chatgpt.md | ChatGPT optimization |
| references/platform-perplexity.md | Perplexity strategies |
| references/platform-google-ai-overviews.md | Google AIO optimization |
| references/llm-tracking-tools.md | LLM visibility tools |
| references/competitor-citation-gap.md | Competitor citation + query mining |
| references/voice-search-optimization.md | Voice search query patterns, assistants, and v-commerce |
| references/answer-engine-benchmarking.md | Citation benchmarking framework and KPI definitions |
| references/local-ai-search.md | Local business optimization for AI search engines |
| project-aeo-monitoring-tools | Custom monitoring infrastructure (build vs buy) |
Templates
| Template | Purpose |
|---|---|
| assets/audits/search-visibility-audit.md | Baseline audit |
| assets/audits/ai-search-content-audit.md | AI visibility audit |
| assets/audits/competitor-citation-gap-audit.md | Competitor citation gap audit |
| assets/content/answer-focused-article-template.md | Article template |
| assets/content/ai-answer-diagnosis-template.md | Structured diagnosis output |
| project-aeo-monitoring-tools/assets/setup/minimal-setup-guide.md | Monitoring setup guide |
International Markets
This skill uses US/English market defaults. For international AI search optimization:
| Need | See Skill |
|---|---|
| Regional AI platforms (Baidu AI, Yandex) | marketing-geo-localization |
| Non-English content optimization | marketing-geo-localization |
| Regional search behavior differences | marketing-geo-localization |
| Multilingual schema markup | marketing-geo-localization |
Auto-triggers: When your query mentions a specific country, region, language, or non-US AI platforms, both skills load automatically.
Related Skills
| Skill | Purpose |
|---|---|
| project-aeo-monitoring-tools | Build custom AEO monitoring infrastructure (APIs, pipelines, dashboards) — engineering skill |
| marketing-seo-complete | Traditional SEO |
| marketing-content-strategy | Content planning |
| software-frontend | SSR implementation |