# AEO/GEO intelligence Human Guide

## What This Is For
Strategy module for Answer Engine / Generative Engine Optimization — audits AI visibility, restructures content for citation, runs entity-consistency checks across Knowledge Graph. It gives the agent a clearer input/output frame for search and SEO workflows: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the AEO/GEO intelligence agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for AEO/GEO intelligence.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the AEO/GEO intelligence guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- **AI Visibility**: Questions about how a brand, product, or person appears in AI-generated answers (ChatGPT, Perplexity, **Google AI Mode**, Google AI Overviews, Copilot, Gemini, Claude)
- **Answer Engine Optimization (AEO)**: Optimizing content so it gets selected as a source for AI-generated answers
- **Generative Engine Optimization (GEO)**: Structuring content and entities so generative AI platforms accurately represent a brand
- **Citation Tracking**: Monitoring which sources AI models cite when answering queries related to a brand or industry
- **Entity Consistency**: Ensuring brand information is uniform across all knowledge sources that AI models train on or retrieve from
- **Knowledge Graph Optimization**: Improving how a brand is represented in Google Knowledge Graph, Wikidata, and other structured knowledge bases
- **Structured Data for AI**: Implementing schema markup and structured data specifically to improve AI comprehension and citation likelihood
- For Google's *other* AI systems (Gemini app training, Vertex AI grounding outside Search): use the **Google-Extended** user agent in robots.txt. This is a distinct control from Googlebot.
- **Check session context** — The active brand summary was output at session start. Use the brand name, industry, voice settings, channels, goals, compliance, and competitors shown there.
- **If you need the full profile**, read: `~/.claude-marketing/brands/{slug}/profile.json`
- **Apply brand voice** — Formality, energy, humor, authority levels must shape all content tone and word choices
- **Check compliance** — Auto-apply rules for brand's target_markets and industry using `skills/context-engine/compliance-rules.md`

## Decision Points And Nuance
The original skill emphasizes: When to Use This Skill, Brand Context (Auto-Applied), Required Context, Capabilities, Process, Reference Files, Output Formats, Edge Cases, Brand with Negative AI Perception, New Brand with Zero AI Visibility.

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- **Apply brand voice** — Formality, energy, humor, authority levels must shape all content tone and word choices
- Do not ask the user for information that already exists in their brand profile.
- Identify patterns: Which query types yield citations? Which don't?
- **Don't try to "trick" AI into citing you** with stuffed content or fake authority signals. AI platforms detect and demote this faster than traditional search.
- **Gemini**: Test via gemini.google.com, note any "I don't have enough info" responses.
- **Avoid hedging language**: "Arguably" and "some experts say" reduce citation likelihood
- Earn Wikipedia references (do NOT edit Wikipedia directly)
- Every claim MUST have a reference (URL to a reliable source)

## Copy-And-Paste Prompt
```text
Use the AEO/GEO intelligence human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the indranilbanerjee/digital-marketing-pro skill entry for `aeo-geo`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# AEO/GEO Intelligence

## When to Use This Skill

Activate this module when the user's request involves any of the following:

- **AI Visibility**: Questions about how a brand, product, or person appears in AI-generated answers (ChatGPT, Perplexity, **Google AI Mode**, Google AI Overviews, Copilot, Gemini, Claude)
- **Answer Engine Optimization (AEO)**: Optimizing content so it gets selected as a source for AI-generated answers
- **Generative Engine Optimization (GEO)**: Structuring content and entities so generative AI platforms accurately represent a brand
- **Citation Tracking**: Monitoring which sources AI models cite when answering queries related to a brand or industry
- **Entity Consistency**: Ensuring brand information is uniform across all knowledge sources that AI models train on or retrieve from
- **Knowledge Graph Optimization**: Improving how a brand is represented in Google Knowledge Graph, Wikidata, and other structured knowledge bases
- **Structured Data for AI**: Implementing schema markup and structured data specifically to improve AI comprehension and citation likelihood

**Trigger phrases**: "AI visibility," "how does ChatGPT describe my brand," "Perplexity results," "AI Mode optimization," "AI Overview optimization," "answer engine," "generative engine," "LLM optimization," "AI citations," "entity consistency," "Knowledge Graph"

**Google AI Mode (May 2026 — treat as a distinct surface)**: At Google I/O on 19 May 2026 AI Mode became the default search experience for opted-in users, crossed ~1B MAUs, and switched to Gemini 3.5 Flash as the base model. AI Mode is **not** the same as AI Overviews — it is a separate conversational tab with deeper reasoning, multi-turn follow-ups, and a citation pattern that frequently diverges from AI Overviews for the same query. Brands must audit AI Mode independently. Practical implication: an AEO program that only tests AI Overviews + ChatGPT + Perplexity now has a measurable blind spot.

**Additional I/O 2026 announcements that change AEO scope** ([source: blog.google/products-and-platforms/products/search/search-io-2026](https://blog.google/products-and-platforms/products/search/search-io-2026/)):

- **AI Overview → AI Mode follow-up flow** is live worldwide (desktop + mobile) — users can ask a follow-up directly from an AI Overview and flow into a conversational AI Mode session. AEO implication: the *first* impression in an AI Overview is now also a gateway to multi-turn citation. Optimize for being the foundational citation, not just the brief snippet.
- **Personal Intelligence in AI Mode** is expanding to ~200 countries and 98 languages, no subscription required, with Gmail / Photos / Calendar connections. AEO implication: AI answers are increasingly personalized — generic brand-search results will be reweighted against the user's own context. Brand schema completeness and entity consistency (NAP, services, hours) matter even more.
- **AI Information Agents** (user-created, monitoring blogs/news/social 24/7) launch for AI Pro & Ultra subscribers in summer 2026. AEO implication: brands that publish structured, dated updates on owned channels will be more legible to user-configured agents than those relying on third-party PR pickup.

**Official Google guidance on AI search optimization** (updated 15 May 2026 — [Google AI Optimization Guide](https://developers.google.com/search/docs/fundamentals/ai-optimization-guide)):

- **No `llms.txt` file is needed.** Google's official position: "You don't need to create new machine readable files, AI text files, markup, or Markdown to appear in generative AI search." Do not waste time generating `llms.txt` for Google AI Features. (Other AI search engines may or may not consume it; current Anthropic / OpenAI / Perplexity public positions are also that they do not require it. Document any client pressure to ship `llms.txt` as a low-priority deliverable with no measurable upside.)
- **No special AI-specific schema is needed.** "Structured data isn't required for generative AI search, and there's no special schema.org markup you need to add." Schema continues to matter for classic SEO and rich results.
- **Eligibility is standard Search.** "To be eligible to be shown in generative AI features on Google Search, a page must be indexed and eligible to be shown in Google Search with a snippet, fulfilling the Search technical requirements."

**Opt-out and AI training controls** ([Google AI Features doc](https://developers.google.com/search/docs/appearance/ai-features)):

- For AI Overviews and AI Mode (inside Google Search): use existing snippet directives — `nosnippet`, `data-nosnippet`, `max-snippet`, `noindex`. Robots.txt for Googlebot is the canonical control. **There is no AI-specific robots/meta directive.**
- For Google's *other* AI systems (Gemini app training, Vertex AI grounding outside Search): use the **Google-Extended** user agent in robots.txt. This is a distinct control from Googlebot.
- **NEW (3 June 2026):** Search Console now ships an **opt-out toggle** at the property level — flip it to exclude the site from grounding AI Overviews / AI Mode responses without editing robots.txt. See `/digital-marketing-pro:gsc-ai-performance` for the decision framework on when to use it.

**EU AI Act Article 50 (applicable 2 August 2026)** — for AI-generated marketing content surfaced in EU markets, see `skills/context-engine/eu-code-of-practice.md` for the voluntary Code of Practice (WG1 providers / WG2 deployers) and the C2PA `c2pa.ai-disclosure` assertion path. Compliance is plugin-level and applies to `c2pa-metadata` outputs.

## Brand Context (Auto-Applied)

Before producing any marketing output from this module:

1. **Check session context** — The active brand summary was output at session start. Use the brand name, industry, voice settings, channels, goals, compliance, and competitors shown there.
2. **If you need the full profile**, read: `~/.claude-marketing/brands/{slug}/profile.json`
3. **Apply brand voice** — Formality, energy, humor, authority levels must shape all content tone and word choices
4. **Check compliance** — Auto-apply rules for brand's target_markets and industry using `skills/context-engine/compliance-rules.md`
5. **Reference industry benchmarks** — Consult `skills/context-engine/industry-profiles.md` for the brand's industry
6. **Use platform specs** — Reference `skills/context-engine/platform-specs.md` for character limits and format requirements
7. **Check campaign history** — Run `python "${CLAUDE_PLUGIN_ROOT}/scripts/campaign-tracker.py" --brand {slug} --action list-campaigns` before planning new work
8. **If no brand exists**, say: "No brand profile found. Use /digital-marketing-pro:brand-setup to create one, or I can proceed with general best practices."
9. **Check brand guidelines** — If `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` exists, load and enforce: `restrictions.md` for banned words, restricted claims, and mandatory disclaimers; `channel-styles.md` for channel-specific tone overrides (may differ from base voice); `messaging.md` for approved key messages, taglines, and positioning language; `voice-and-tone.md` for detailed voice rules beyond the 4 numeric scores. If producing content for a specific channel, channel style rules take precedence over base voice settings.

Do not ask the user for information that already exists in their brand profile.

## Required Context

Before executing AEO/GEO work, gather:

1. **Brand Identity**: Official brand name, key products/services, unique value propositions, and brand positioning
2. **Current AI Footprint**: Ask the user if they have tested how AI platforms currently describe their brand (or offer to audit)
3. **Target Queries**: The questions and topics the brand wants to be cited for in AI-generated answers
4. **Existing Content Assets**: Website URL, blog, knowledge base, Wikipedia presence, schema markup status
5. **Competitive Landscape**: Key competitors who may already have strong AI visibility
6. **Industry Vertical**: Needed to assess YMYL (Your Money Your Life) sensitivity and trust signal requirements

If the user cannot provide all context, proceed with what is available and flag gaps as recommendations.

**Minimum viable context**: Brand name and website URL. Everything else can be inferred or discovered during the audit process.

## Capabilities

- **AI Visibility Audit**: Systematic testing of how a brand appears across the 6 canonical surfaces — Google AI Mode, Google AI Overviews, ChatGPT, Perplexity, Gemini, and Copilot — for target queries (scored with the standard defined in `/digital-marketing-pro:aeo-audit`)
- **Citation Optimization**: Restructuring content to maximize the probability of being cited as a source in AI-generated responses
- **Entity Consistency Audit**: Cross-referencing brand information across Google Knowledge Graph, Wikidata, Wikipedia, Crunchbase, LinkedIn, and industry databases to identify inconsistencies
- **LLM Content Strategy**: Creating content specifically designed to be ingested and accurately represented by language models
- **AI Answer Monitoring Framework**: Setting up systematic tracking of AI mentions and citations over time
- **Structured Data for AI Citation**: Implementing Organization, Product, FAQ, HowTo, and other schema types that improve AI comprehension
- **Knowledge Graph Optimization**: Improving entity representation in structured knowledge bases
- **Topical Authority Mapping**: Identifying content gaps that prevent a brand from being recognized as an authority by AI models
- **AI-First Content Formatting**: Restructuring existing content with clear definitions, factual statements, and citation-worthy snippets