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AI Engine Optimization - semantic triples, page templates, content clusters for AI citations
Passed 17 of 22 test cases with the skill, and 10 of 22 without it.
and 11 more in the full report
8 fixed9 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a 3-sentence feature summary paragraph for an automated email verification tool called 'AddressCheck' designed for e-commerce marketers.
| Checked | Without skill | With skill |
|---|---|---|
| Follows the Feature -> How -> Outcome structure | Passed | Passed |
| Includes a measurable metric or timeframe in the outcome statement | Missed | Passed |
The instructions your model reads when the skill loads.
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.
┌────────────────────────────────────────────────────────────────┐
│ 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:
AI engines use three main signals to select content for answers:
test cases passed, vs 10 / 22 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.