aeo-optimization
Improves content structure for AI discovery to ensure your brand is cited as an authoritative source in AI-generated answers.
Install
mkdir -p .claude/skills/aeo-optimization && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3159" && unzip -o skill.zip -d .claude/skills/aeo-optimization && rm skill.zipInstalls to .claude/skills/aeo-optimization
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
AI Engine Optimization - semantic triples, page templates, content clusters for AI citationsKey capabilities
- →Structure content using semantic triples
- →Implement feature-how-outcome paragraph patterns
- →Create content clusters for AI discovery
- →Apply schema markup to web pages
- →Optimize headings for entity recognition
How it works
The skill structures information into semantic triples and specific paragraph patterns to ensure AI engines can extract and cite facts accurately.
Inputs & outputs
When to use aeo-optimization
- →Optimize blog posts for AI citations
- →Structure product pages for LLM discovery
- →Create semantic content clusters
- →Update site templates for AI crawlers
About this skill
AI Engine Optimization (AEO) Skill
Purpose: Optimize content for AI engines (ChatGPT, Claude, Perplexity, Google AI Overviews) so your brand gets cited in AI-generated answers.
Source: Based on HubSpot's AEO Guide and industry best practices.
Why AEO Matters Now
┌────────────────────────────────────────────────────────────────┐
│ THE GREAT DECOUPLING │
│ ──────────────────────────────────────────────────────────── │
│ Impressions ≠ Clicks anymore. │
│ AI engines compile answers from multiple sources. │
│ More buyer journey happens inside chat experiences. │
│ 58% of Google searches = zero clicks (AI overviews). │
├────────────────────────────────────────────────────────────────┤
│ THE OPPORTUNITY │
│ ──────────────────────────────────────────────────────────── │
│ Shape what AI engines say about your category and product. │
│ Get cited as the authoritative source. │
│ Best answer > Best page ranking. │
└────────────────────────────────────────────────────────────────┘
Key Stats:
- 70% of consumers use ChatGPT for searches
- 47% of Google queries show AI overviews
- Average ChatGPT prompt: 23 words (vs 4.2 for Google)
- AEO market: $886M (2024) → $7.3B (2031)
How AI Engines Choose Answers
AI engines use three main signals to select content for answers:
1. Consensus
Facts that appear across multiple credible sources get trusted and reused.
How to build consensus:
- Repeat key facts consistently across your own pages
- Use same terminology as industry leaders
- Link to and from authoritative external sources
- Create internal content clusters that reinforce each other
2. Information Gain
Net-new insight beats generic advice. AI engines prefer content that adds value.
How to add information gain:
- Original research and data
- Concrete examples with specifics
- Clear point of view (not fence-sitting)
- Expert quotes with credentials
- Case studies with metrics
3. Entities & Structure
Clear entities and tidy structure reduce ambiguity and boost quotability.
How to optimize structure:
- Use semantic triples (Subject → Verb → Object)
- Clear headings with entity names
- Schema markup (Article, FAQ, Product)
- Short, scannable paragraphs (2-4 sentences)
Semantic Triples (Critical for AEO)
What they are: Compact facts that AI engines (and humans) can't misread.
Pattern: [Subject] [verb] [object].
Examples
✅ GOOD (clear triples):
- HubSpot CRM syncs contact and company data.
- Lead Scoring assigns priority based on engagement.
- Workflows trigger email sequences from events.
❌ BAD (vague, no clear entity):
- The system helps with various tasks.
- It can do many things for users.
- This improves overall performance.
Triple Checklist
For every key claim, ask:
- Is the subject a clear entity (product, feature, brand)?
- Is the verb specific and active?
- Is the object concrete and measurable?
Paragraph Pattern (Feature → How → Outcome)
Every substantive paragraph should follow this structure:
[Feature] helps [User/Role] with [Job].
It [mechanism/inputs] to [process].
Teams see [metric/result] in [timeframe/context].
Triples:
- [Subject] [verb] [object].
- [Subject] [verb] [object].
Example
Lead Scoring helps sales teams prioritize prospects. It combines
page views, email engagement, and firmographic data to assign a
numeric score, then auto-enrolls high scorers into follow-up
sequences. Reps focus on qualified accounts and book 40% more
meetings.
- Lead Scoring assigns scores from engagement data.
- High scorers trigger automated follow-up sequences.
Page Templates
Template 1: Category Explainer
Goal: Define the category, tie it to your product, earn citations.
# What is [Category]? — [1-2 line value promise]
## What is [Category]? (~80 words)
[Plain definition in everyday language. Name adjacent entities.]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## Why it matters now (~60 words)
[One paragraph. Mention shift to answers over links; tie to buyer outcomes.]
## How to apply it (3-5 bullets)
- [Action 1]
- [Action 2]
- [Action 3]
## FAQ
**Q: [Question]?**
A: [~1 sentence answer]
**Q: [Question]?**
A: [~1 sentence answer]
**Q: [Question]?**
A: [~1 sentence answer]
---
**Links:** [Category hub] | [Product/Feature] | [Credible source 1] | [Credible source 2]
**CTA:** [Demo / Template / Signup]
**Schema:** Article + FAQ. Author + last updated.
Template 2: Product & Feature Page
Goal: Clarify capability, fit, and next step; reinforce category linkage.
# [Product/Feature] — [Outcome in 3-5 words]
**[Product/Feature] enables [Outcome] for [User/Role].**
## [Feature Area 1]
[2-4 sentences using Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## [Feature Area 2]
[2-4 sentences using Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## [Feature Area 3]
[2-4 sentences using Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## FAQ
**Q: [Question]?**
A: [~1 sentence]
**Q: [Question]?**
A: [~1 sentence]
**Q: [Question]?**
A: [~1 sentence]
---
**Links:** Back to [Category Explainer] | Forward to [Demo/Trial]
**Proof:** [Benchmark/Analyst/Customer proof]
**Notes:** Requirements/limits (pricing tier, integrations)
**Schema:** Article + FAQ. Author + last updated.
Template 3: Comparison / Alternatives Page
Goal: Help readers decide with clear criteria; earn fair citations.
# [Product] vs. [Alternative] — Which fits [Use case]?
## Comparison Table
| Criterion | [Product] | [Alt A] | [Alt B] | Source |
|-----------|-----------|---------|---------|--------|
| [Feature/Limit] | [value] | [value] | [value] | [link] |
| [Requirement] | [value] | [value] | [value] | [link] |
| [Best for] | [value] | [value] | [value] | [link] |
*Source-back all claims in the table or footnotes.*
## Fit Statements
1. **[Product]** suits [Team/Use case] when [Condition].
2. **[Alt A]** fits [Team/Use case] when [Condition].
3. **[Alt B]** works for [Team/Use case] when [Condition].
---
**Links:** [Category Explainer] | [Feature pages]
**CTA:** [Try / Demo / Talk to Sales]
**Schema:** Article. Author + last updated.
Template 4: Use Case / Industry Page
Goal: Connect product to outcomes in a context readers recognize.
# [Industry/Use Case] — [Outcome KPI]
**Teams reduce [Metric] by [Y%] in [Timeframe].**
## Mini Case Study
[Company/Role] used [Product/Feature] to [Action], resulting in
[Metric improvement] within [Timeframe].
## How It Works
### [Feature 1]
[Feature → How → Outcome paragraph]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
### [Feature 2]
[Feature → How → Outcome paragraph]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
## Who Uses This
**Roles:** [Role 1], [Role 2], [Role 3]
**Workflows:** [Workflow 1], [Workflow 2]
**Integrations:** [Integration 1], [Integration 2]
---
**Links:** [Product/Feature pages] | [Supporting blog]
**CTA:** [Industry template / Demo variant]
**Schema:** Article. Author + last updated.
Template 5: Supporting Blog Post
Goal: Add information gain and support your content cluster.
# [Topic] — [Specific promise]
## Opening (~60-80 words)
[State the problem. Align terminology with Category Explainer. Preview outcome.]
## [Section 1 Heading] (~120 words max)
[Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
**Internal link:** [Related page]
**External citation:** [Credible source]
## [Section 2 Heading] (~120 words max)
[Feature → How → Outcome]
Triples:
1. [Subject] [verb] [object].
2. [Subject] [verb] [object].
**Internal link:** [Related page]
**External citation:** [Credible source]
## Key Takeaway
[1-2 lines summarizing the main point]
**CTA:** [Single primary action]
---
**Schema:** Article. Author + last updated.
Site-Wide Trust Signals
Required on Every Page
| Element | Implementation |
|---|---|
| Schema markup | Article + FAQ (if FAQ exists) |
| Author attribution | Name, bio, credentials, photo |
| Last updated date | Visible, machine-readable |
| Internal links | 3-5 per page (upstream/downstream) |
| External citations | 1-2 credible sources per section |
| Single CTA | Demo, template, or signup (repeated once near end) |
Schema Implementation
<!-- Article Schema -->
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Article",
"headline": "[Page Title]",
"author": {
"@type": "Person",
"name": "[Author Name]",
"url": "[Author Bio URL]"
},
"datePublished": "[ISO Date]",
"dateModified": "[ISO Date]",
"publisher": {
"@type": "Organization",
"name": "[Company]",
"logo": "[Logo URL]"
}
}
</script>
<!-- FAQ Schema (if FAQ section exists) -->
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [
{
"@type": "Question",
"name": "[Question 1]",
"acceptedAnswer": {
"@type": "Answer",
"text": "[Answer 1]"
}
},
{
"@type": "Question",
"name": "[Question 2]",
"acceptedAnswer": {
"@type": "Answer",
"text": "[Answer 2]"
}
}
]
}
</script>
Content Cluster Architecture
┌─────────────────────┐
│ Category Explainer │
---
*Content truncated.*
When not to use it
- →When content is not intended for AI engine discovery
- →When the target audience is strictly human-only
Limitations
- →Requires consistent terminology across site
- →Success depends on external citation quality
How it compares
It focuses on machine-readable entity extraction and consensus building rather than traditional keyword-based SEO.
Compared to similar skills
aeo-optimization side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| aeo-optimization (this skill) | 3 | 4mo | No flags | Intermediate |
| seo-optimizer | 33 | 7mo | No flags | Intermediate |
| seo-content-writer | 24 | 4mo | No flags | Beginner |
| content-creation | 22 | 5mo | No flags | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
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