Skip to content
Agentmart
Submit a tool

aeo-optimization

AI Engine Optimization - semantic triples, page templates, content clusters for AI citations

Skill by alinaqi

IndexedMIT★ 711
Write a review

Chalk Labs

Need help deploying aeo-optimization?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/alinaqi-aeo-optimization

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

AI Engine Optimization - semantic triples, page templates, content clusters for AI citations

Use cases: writing

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/aeo-optimization

What's inside

Skill name
aeo-optimization
Description
AI Engine Optimization - semantic triples, page templates, content clusters for AI citations
License
MIT
Instructions
549 lines in SKILL.md · view on GitHub

Agent Skills spec issues

  • body: 549 lines (spec recommends under 500)

Files (1)

  • SKILL.md

SKILL.md (first lines)

# 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](https://www.hubspot.com/aeo) 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

```markdown

From alinaqi/maggy, MIT.

More from alinaqi/maggy

Signals

Stars
711
Forks
61
Open issues
0
Last commit (this folder)
Apr 7, 2026 (6 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

Same skill elsewhere

Copies of this SKILL.md published by others; search shows only one of them.

More from alinaqi

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get aeo-optimization running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying aeo-optimization?

CallGet help
Cite this page

aeo-optimization skill. Agent Mart. https://agentmart.dev/skills/alinaqi-aeo-optimization (last updated 2026-10-24)