Answer Engine Optimization skill
The extraction method Okara’s GEO Agent uses to make content quotable: a direct answer in the first 60 words, self-contained sections, checkable facts, and the right schema.
Download the methodology, see how the agent restructures a page for extraction, or run it live inside the GEO Agent.
- Category
- GEO
- Agent
- GEO Agent
- Format
- answer-engine-optimization.md
- Price
- Free to download
The skill file
--- name: answer-engine-optimization description: Structure content so answer engines can extract it — a direct answer up top, self-contained sections, checkable facts, and schema that removes ambiguity. owner: Okara GEO Agent --- # Answer Engine Optimization Answer engines don't read a page the way a person does. They extract passages. AEO is the discipline of making your passages extractable, correct, and attributable — so the engine quotes you rather than paraphrasing someone else.
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About this skill
What is the Answer Engine Optimization?
The Answer Engine Optimization skill is the exact approach Okara’s GEO Agent follows to make a page quotable by AI answer engines. It writes one question per section, puts a complete 40–60 word answer directly under the heading, and makes every section self-contained — because an extracted passage arrives without the paragraphs that surrounded it.
It’s written as a SKILL.md, a plain-language instruction format that people and AI agents can both follow. Use it when your pages rank but never get quoted, or when you are writing new content and want it built for extraction from the start.
Downloading the instructions is free with an Okara account. Running the skill across your site — pages restructured, schema applied, freshness maintained — is part of the GEO Agent.
Example
See it in action
You ask: “We rank on page one for this query and a thinner competitor page keeps getting quoted instead.”
Agent does: It reads the page the way a parser does and finds the problem immediately: the answer to the query is in paragraph five, after four paragraphs of context, and every section depends on the one before it for meaning. Nothing on the page can stand alone, so nothing can be lifted. The fix is structural — a complete 40 to 60 word answer directly under a heading phrased as the question people actually ask, then supporting detail below it. Sections get rewritten to be self-contained, the comparison buried in prose becomes a table, and the vague claims get replaced with dated, sourced numbers, because specific verifiable statements get quoted while adjectives get discarded. FAQPage schema goes on to remove parsing ambiguity, and it maps the follow-up questions the engine will chain to next — which is usually where the next citation comes from.
How it works
From input to output
- 1
You point at the page
Share the page or topic and the question it should be answering.
- 2
Okara restructures for extraction
The GEO Agent moves the direct answer to the top and makes every section stand alone.
- 3
It hardens the facts
Vague claims become dated, sourced, checkable statements, and prose becomes tables where that extracts better.
- 4
You ship schema and follow-ups
The right JSON-LD goes on, and the follow-up questions engines chain to become your next sections.
What's included
Everything it covers
Question-shaped headings
Headings phrased as the question asked, mapping directly to the query being answered.
Direct answer block
A complete 40–60 word answer immediately under the heading, built as the extraction target.
Self-contained sections
Passages that make sense alone, because an extract arrives without its neighbours.
Structured formats
Tables, ordered steps, and definitions where they extract more cleanly than prose.
Schema markup
FAQPage, HowTo, Article, or Product JSON-LD that removes ambiguity for the parser.
Freshness plan
Visible dates and an update cadence, since answer engines discount stale content heavily.
Use cases
When to reach for it
- Get quoted for queries where you rank but a thinner page gets cited.
- Build new content for extraction rather than retrofitting it later.
- Convert narrative pages into passages an engine can lift.
- Add the schema that makes your structure unambiguous.
- Cover the follow-up questions engines chain to after the first answer.
Frequently Asked Questions
Related skills
Pair it with these skills
AI Overviews
The GEO playbook Okara’s GEO Agent uses to get your brand cited in AI answers across ChatGPT, Perplexity, Gemini, and Google AI Overviews.
--- name: ai-overviews description: Optimize a page to get cited in AI answers — Google AI Overviews, ChatGPT, Perplexity, and Gemini — not just ranked in blue links. owner: Okara GEO Agent --- # AI Overviews Generative Engine Optimization (GEO): make your brand the source AI assistants cite when they answer questions in your space, not just a link on page one.
llms.txt
The GEO playbook Okara’s GEO Agent uses to publish and maintain an llms.txt file — the machine-readable index that tells AI crawlers and assistants which of your pages matter and what they mean.
--- name: llms-txt description: Create and maintain an llms.txt file so AI crawlers and assistants can find, understand, and cite your most important content. owner: Okara GEO Agent --- # llms.txt A curated, machine-readable index at the root of your site that tells AI crawlers and assistants which pages matter and what they mean — so your best content is the content models read, trust, and cite.
AI Detection
The GEO playbook Okara’s GEO Agent uses to check whether your content reads as AI-generated and reshape it into natural, high-quality writing that protects your brand and earns AI citations.
--- name: ai-detection description: Check whether content reads as AI-generated and reshape it into natural, high-quality writing that protects your brand and earns AI citations. owner: Okara GEO Agent --- # AI Detection Detect the patterns that make writing read as machine-generated, then fix them — so your content sounds genuinely written, holds up to scrutiny, and is the kind of source AI assistants trust and cite.