AEO (Answer Engine Optimization) System

Get AI assistants — ChatGPT, Perplexity, Claude, Gemini — to recommend your brand when people ask purchase-intent questions.

What This Is

AEO is the discipline of optimizing for AI-powered answer engines the same way SEO optimizes for search engines. When someone asks Perplexity "what's the best magnesium supplement for sleep?" — AEO determines whether your brand gets named.

This skill gives an OpenClaw agent the ability to:

1. Audit a brand's current AEO infrastructure across all 7 layers
2. Map which brands AI platforms recommend (and in what position) for any category
3. Track position changes week over week
4. Build the missing infrastructure (Answer Hub, brand-facts.json, schema, citations)
5. Maintain the system with a weekly 90-minute protocol

When to Load This Skill

• User asks to "run an AEO audit" for a brand or URL
• User asks "which brands are being recommended by AI for [category]?"
• User asks to "build an Answer Intent Map" for a category
• User asks to check a brand's Answer Hub, brand-facts.json, or schema markup
• User asks to track AI recommendation positions over time
• User asks to run the "weekly AEO maintenance protocol"

The 7-Layer AEO Framework

/.well-known/brand-facts.json

Prerequisites

Required:

• PERPLEXITY_API_KEY

  — enables direct API queries (get free at perplexity.ai/settings/api)
• Node.js v18+ (for the

  answer-intent-map.js

  script)

Optional:

• OPENAI_API_KEY

  — enables ChatGPT query automation

• BRAVE_API_KEY

  — enables web searches for infrastructure checks

Without API keys: The skill runs in "manual-assist" mode — generates the queries, provides a blank log template, and analyzes results you paste in.

Core Workflows

Workflow 1: Full AEO Audit

Trigger: "Run an AEO audit for [brand URL]"

Steps:

1. Fetch and analyze the brand's website for AEO infrastructure:

   • Check for Answer Hub page (

     /guides/

     or similar long-form page)
   • Check for Brand-Facts page (

     /brand-facts

     )
   • Check for machine-readable data (

     /.well-known/brand-facts.json

     )
   • Audit schema markup on product pages (via Rich Results API or web_fetch)
   • Check for a Wikidata entry
   • Check Google Merchant Center eligibility signals

2. Score each of the 7 layers (0–3 scale):

   • 0 = Doesn't exist
   • 1 = Exists but incomplete or outdated
   • 2 = Exists, functional, minor gaps
   • 3 = Complete, current, optimized

3. Generate a gap analysis report with:

   • Current score per layer
   • Priority order for implementation
   • Specific action items for each missing layer

Output: Markdown report saved as

aeo-audit-[brand]-[date].md

Workflow 2: Answer Intent Map

Trigger: "Build an Answer Intent Map for [category]" or run

scripts/answer-intent-map.js

Steps:

1. Generate query list from four types:

   • Category queries: "best [product] for [use case]" (10–15 queries)
   • Comparison queries: "[brand] vs [competitor]" (10 queries)
   • Brand queries: "is [brand] worth it" (5 queries)
   • Educational queries: "does [ingredient] help with [condition]" (10 queries)

2. For each query, query available platforms:

   • Perplexity API (structured JSON response with citations)
   • OpenAI API (text response — brand names extracted by parser)
   • Browser fallback for Claude and Gemini

3. Parse responses to extract:

   • Brand names mentioned (position 1, 2, 3)
   • Source URLs cited
   • Key verbatim quotes

4. Write results to JSON data file + Markdown summary report

Output:

answer-intent-map-[category]-[date].json

.md

Run the script:

node scripts/answer-intent-map.js \
  --category "magnesium supplements" \
  --brand "MyBrand" \
  --queries 20

# Or with a config file:
node scripts/answer-intent-map.js --config ./aeo-config.json

Workflow 3: Weekly Maintenance Protocol

Trigger: "Run weekly AEO maintenance" or scheduled cron

Steps:

1. Load the brand's Answer Intent Map (top 15 priority queries)
2. Query ChatGPT and Perplexity for each priority query in fresh sessions
3. Compare results against previous week's log (detect position changes)
4. Generate maintenance report:
   • Position changes (up/down/new competitors)
   • New sources being cited this week
   • Recommended Answer Hub updates
5. Check

   brand-facts.json

   for stale

   lastUpdated

   timestamp
6. Check Google Merchant Center for disapprovals (via browser if needed)

Output:

aeo-weekly-report-[date].md

Use the checklist:

templates/weekly-maintenance-checklist.md

Workflow 4: Citation Network Analysis

Trigger: "Analyze AEO citations for [category]"

Steps:

1. Run 20 category queries via Perplexity API (citations returned directly)
2. Extract all unique source URLs from responses
3. Group and count by domain
4. Identify top 10 most-cited external sources in the category
5. Generate outreach priority list

Output: Citation analysis report with target sites ranked by citation frequency

Workflow 5: Infrastructure Build

Trigger: "Build AEO infrastructure for [brand]" or "Set up brand-facts.json"

Steps:

1. Ask for brand details (or load from

   aeo-config.json

   )
2. Generate from templates:

   • brand-facts.json

     →

     templates/brand-facts.json

     (fill placeholders)
   • Answer Hub page →

     templates/answer-hub-template.md

   • Schema markup snippet (JSON-LD for product pages)
3. Provide implementation instructions per asset

Configuration

Create

aeo-config.json

{
  "brandName": "Your Brand Name",
  "brandUrl": "https://yourbrand.com",
  "category": "Magnesium Supplements",
  "priorityQueries": [
    "best magnesium supplement for sleep",
    "best magnesium glycinate supplement",
    "magnesium supplement for anxiety"
  ],
  "competitors": [
    "Competitor Brand A",
    "Competitor Brand B",
    "Competitor Brand C"
  ],
  "answerHubUrl": "https://yourbrand.com/guides/best-magnesium-supplements-2026",
  "brandFactsJsonUrl": "https://yourbrand.com/.well-known/brand-facts.json"
}

Output Files

aeo-audit-[brand]-[date].md

answer-intent-map-[category]-[date].json

answer-intent-map-[category]-[date].md

aeo-weekly-report-[date].md

citation-analysis-[category]-[date].md

Usage Examples

# Full infrastructure audit
"Run an AEO audit for mybrand.com"

# Build competitive intelligence
"Build an Answer Intent Map for the magnesium supplement category"

# Quick position check
"Check if mybrand.com is being recommended by Perplexity for 'best magnesium for sleep'"

# Weekly maintenance
"Run the weekly AEO maintenance protocol for my brand"

# Citation analysis
"Which sources does Perplexity cite most for collagen supplement recommendations?"

# Generate brand-facts.json
"Generate the brand-facts.json template for [brand details]"

# Scoring review
"Score my AEO infrastructure for mybrand.com on all 7 layers"

Platform Limitations

For Claude/Gemini: the skill generates the query list and a blank log template; use the browser tool to collect results.

Rate limits: Perplexity free tier ≈ 20 requests/minute. For 50+ queries, add

--delay 3000

File Structure

aeo-system/
├── SKILL.md                              ← This file
├── README.md                             ← Human-readable overview
├── scripts/
│   └── answer-intent-map.js              ← Core query automation script
└── templates/
    ├── answer-hub-template.md            ← Answer Hub page template
    ├── brand-facts.json                  ← Machine-readable brand data template
    └── weekly-maintenance-checklist.md  ← 90-minute weekly protocol

AEO System v1.0 — February 2026 A product by Carson Jarvis (@CarsonJarvisAI)