Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →borghei/aeo
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers.
Passed 20 of 22 test cases with the skill, and 14 of 22 without it.
and 6 more in the full report
6 fixed14 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
We want to programmatically evaluate an existing markdown article located at `./articles/data-pipeline.md` to check its compliance with answer engine citation patterns using the built-in CLI suite. We prefer simple formatted markdown output rather than raw text. What command and flags execute this check?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies aeo_content_auditor.py as the execution script | Missed | Passed |
| Supplies the file target using the path command line argument | Passed | Passed |
| Specifies markdown as the output format flag value | Passed | Passed |
The instructions your model reads when the skill loads.
End-to-end practice of optimizing content to be cited by LLMs when they generate answers. Covers the technical foundations (how LLMs select sources), content structuring patterns (Q&A schema, citation-worthy patterns), measurement (which content gets cited, by which LLM, how often), and the strategic positioning that differentiates AEO from traditional SEO and from AI-SEO.
This skill is provider-aware but provider-agnostic: works for content optimized for ChatGPT, Claude, Perplexity, Gemini, Copilot, and emerging AI surfaces.
| Situation | Skill applies |
|---|---|
| Designing content strategy that targets LLM citation | Yes — start with AEO fundamentals |
| Auditing existing content for LLM citability | Yes — scripts/aeo_content_auditor.py |
| Adding Q&A schema to content | Yes — scripts/schema_qa_generator.py |
| Tracking which content gets cited by LLMs | Yes — scripts/citation_extractor.py |
| Choosing between AEO and traditional SEO investment | Yes — see AEO vs SEO vs AI-SEO |
| Ranking in Perplexity / Google AI Overviews | Use marketing/ai-seo |
| Traditional SEO (rank in Google search results) | Use marketing/seo-specialist |
Three distinct (but overlapping) practices. Confusing them leads to wasted investment.
| Practice | Optimizes for | Surface | Success metric |
|---|---|---|---|
| Traditional SEO | Google / Bing rankings | SERPs (organic blue links) | Position, clicks |
| AI-SEO | AI search engines | Perplexity, Google AI Overviews, You.com | Position in AI search results, traffic from citations |
| AEO (this skill) | LLM citation in answers | ChatGPT, Claude, Gemini, Copilot answers | Citation rate, brand mention in LLM outputs |
For most B2B brands:
Optimize content for all three simultaneously; the techniques substantially overlap.
test cases passed, vs 14 / 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.