aeo-audit
Answer Engine Optimization (AEO) audit methodology for LLM visibility. Use when auditing brands for ChatGPT/Gemini mentions, checking LLM citations, analyzing AI search visibility, or when user mentions "AEO", "LLM visibility", "ChatGPT mentions", "Gemini citations", or "AI search optimization".
Best use case
aeo-audit is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Answer Engine Optimization (AEO) audit methodology for LLM visibility. Use when auditing brands for ChatGPT/Gemini mentions, checking LLM citations, analyzing AI search visibility, or when user mentions "AEO", "LLM visibility", "ChatGPT mentions", "Gemini citations", or "AI search optimization".
Teams using aeo-audit should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/aeo-audit/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How aeo-audit Compares
| Feature / Agent | aeo-audit | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Answer Engine Optimization (AEO) audit methodology for LLM visibility. Use when auditing brands for ChatGPT/Gemini mentions, checking LLM citations, analyzing AI search visibility, or when user mentions "AEO", "LLM visibility", "ChatGPT mentions", "Gemini citations", or "AI search optimization".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# AEO Audit Methodology This skill provides the complete Answer Engine Optimization protocol for auditing and optimizing brand visibility in LLM-powered search (ChatGPT, Gemini, Perplexity, etc.). ## CRITICAL: Read Protocol First **BEFORE running ANY audit, you MUST read the AEO Protocol SOP:** ``` Read aeo-protocol-sop.md (key sections): - Lines 1-200: Core methodology - Lines 850-900: First 50 Words Audit (CRITICAL) - Lines 1200-1300: Content gap analysis - Lines 2800-2900: Audit checklist - Lines 3400-3500: Final checklist ``` **Do NOT skip this step.** The protocol is the source of truth. ## Core Concepts ### What is AEO? Answer Engine Optimization ensures brands appear in LLM-generated answers, not just traditional search results. LLMs cite sources differently than Google - they need: - Facts repeated across 3+ authoritative sources (triangulation) - Structured, extractable content - Clear entity establishment - Technical accessibility (SSR, proper robots.txt) ### The Three Search Backends | Engine | Backend | How It Works | |--------|---------|--------------| | ChatGPT | Bing + Memory | 3-layer cache (parametric → memory → live search) | | Gemini | Google Grounding | Real-time Google Search verification | | Google AI Overview | Google SERP | Aggregates top organic results | ## Audit Process ### Step 1: Run Brand Audit Use `run_brand_audit` MCP tool with: - Brand name - Product category (be specific: "hair transplant clinic" not "medical") - Primary competitor (optional) ### Step 2: Discovery Query Testing Test queries people use BEFORE knowing the brand: - "Best [category] in [location]" - "Best [category] for [use case]" - "Top [category] [year]" - "[problem] solution" ### Step 2.5: CRITICAL - Run Key Queries 10 Times Each **LLM responses are non-deterministic.** Single tests are unreliable. For top 2-3 discovery queries, run each **10 times** per LLM and calculate consistency: | Score | Interpretation | |-------|----------------| | 9-10/10 | Strong (locked in) | | 7-8/10 | Good (consistent) | | 5-6/10 | Weak (inconsistent) | | 1-4/10 | Poor (rarely mentioned) | | 0/10 | Invisible (critical) | **A brand at 60% consistency is NOT reliably visible.** ### Step 2.6: Custom Client Queries Beyond standard queries, test client-specific "dream queries": | Query Type | Example | |------------|---------| | Outcome-focused | "[category] if money doesn't matter" | | Problem-aware | "fix bad [category]" | | Fear-based | "safest [category]" | | Lifestyle | "[category] for executives" | | Attribute-specific | "[category] no scars" | **Ask during intake:** "What 3-5 queries do you WANT to own?" For 0% visibility queries → create dedicated landing page. ### Step 3: Competitive Analysis - Check which competitors appear in LLM responses - Identify citation sources (what sites are LLMs pulling from?) - Map competitive tier (don't compare premium to budget) ### Step 4: Gap Analysis For each query where brand is missing: 1. What sources ARE being cited? 2. Is brand mentioned on those sources? 3. What facts are LLMs extracting? 4. What content needs to be created? ### Step 5: First 50 Words Audit (CRITICAL) For every key page: 1. Fetch page content 2. Extract first 50 words of visible body text 3. Check for presence of: - **WHO**: Brand/entity name, credentials - **WHAT**: Core offering/service - **WHERE**: Location - **PRICE**: Pricing tier or specific numbers 4. Score: Pass (3-4) / Partial (2) / Fail (0-1) 5. Document specific rewrites needed **Why this matters:** LLMs weight early content heavily. Facts not in first 50 words often aren't extracted. ## Scoring Framework | Metric | Weight | Measurement | |--------|--------|-------------| | ChatGPT Mentions | 30% | Brand appears in X/8 queries | | Gemini Mentions | 30% | Brand appears in X/8 queries | | Google AI Overview | 20% | Brand in AI Overview snippets | | Citation Quality | 20% | Authoritative sources citing brand | ## Key Audit Queries (Template) 1. `What is [brand]?` - Basic recognition 2. `Best [category] in [location]` - Discovery 3. `[Brand] vs [competitor]` - Comparison 4. `[Brand] reviews` - Reputation 5. `[Brand] pricing` - Commercial intent 6. `Best [category] for [use case]` - Use-case discovery 7. `[Problem] specialist [location]` - Problem-aware discovery 8. `Top [category] [year]` - List inclusion ## Red Flags in Audits - ❌ Brand not mentioned in discovery queries (acquisition problem) - ❌ Competitor mentioned but brand isn't (content gap) - ❌ Incorrect facts in LLM responses (reputation risk) - ❌ No citations to brand's own website (authority problem) - ❌ Only mentioned with competitor comparisons (positioning issue) ## Quick Reference For detailed methodology, see: - [aeo-protocol-sop.md](../../../aeo-protocol-sop.md) - Full protocol - [fuegenix-aeo-audit.md](../../../clients/fuegenix/fuegenix-aeo-audit.md) - Example audit
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