aeo-optimization
AI Engine Optimization - semantic triples, page templates, content clusters for AI citations
Skill by alinaqi
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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.
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About
Use cases: writing
Reviews
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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
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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.
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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
- Repository
- github.com/alinaqi/maggy
- Website
- www.srooter.ai/maggy
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
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Cite this page
aeo-optimization skill. Agent Mart. https://agentmart.dev/skills/alinaqi-aeo-optimization (last updated 2026-10-24)