Generative Engine Optimization Audit skill
The measurement method Okara’s GEO Agent uses to find out what AI engines say about you, which sources they cite, and which fixes actually change the answer.
Download the methodology, see how the agent audits AI answer presence, or run it live inside the GEO Agent.
- Category
- GEO
- Agent
- GEO Agent
- Format
- geo-audit.md
- Price
- Free to download
The skill file
--- name: geo-audit description: Audit how your brand shows up inside AI answers — what the models say about you, which sources they cite, and the specific fixes that change it. owner: Okara GEO Agent --- # Generative Engine Optimization Audit Generative engines answer rather than list. Being cited inside those answers is a different problem from ranking, with different inputs: extractable structure, citable claims, and third-party sources the model already trusts.
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About this skill
What is the GEO Audit?
The GEO Audit skill is the exact approach Okara’s GEO Agent follows to measure how a brand is represented inside AI-generated answers. It builds a stable question set, runs it across several engines, and records three things per answer: whether you are mentioned, how you are described, and which sources were cited — because the citation pattern is where the leverage actually is.
It’s written as a SKILL.md, a plain-language instruction format that people and AI agents can both follow. Use it to establish a baseline before investing in this channel, or to find out why competitors are named in answers about your category and you are not.
Downloading the instructions is free with an Okara account. Running the skill continuously — monthly re-measurement, citation source work, and the on-site fixes — is part of the GEO Agent.
Example
See it in action
You ask: “Our organic traffic is dropping and I have no idea what ChatGPT says about us.”
Agent does: It builds a stable set of forty real buyer questions — category, comparison, and brand-specific — and runs them across ChatGPT, Perplexity, Gemini, Copilot, and AI Overviews, because answers differ enough by engine that a single-engine check misleads. Three things get recorded per answer: whether you appear, how you are described, and what was cited. The description column is where the bad news usually is — in your case two engines state a pricing tier you retired last year, which is worse than absence because it propagates. The citation map then shows a familiar pattern: the same review site and two community threads feed most answers in your category, which means correcting those sources moves more than any on-page change. It also checks whether GPTBot and PerplexityBot can reach you at all, then ranks the fixes: third-party sources first, extractability second, new content for uncovered questions last.
How it works
From input to output
- 1
You give it the domain and questions
Share your site and the questions buyers actually ask in your category.
- 2
Okara runs the set across engines
The GEO Agent queries ChatGPT, Perplexity, Gemini, Copilot, and AI Overviews with the same stable question set.
- 3
It records presence, accuracy, and citations
You learn whether you appear, how you are described, and which sources the models are leaning on.
- 4
You fix in priority order
Third-party sources first, extractability next, then new content — re-measured monthly.
What's included
Everything it covers
Stable question set
Thirty to fifty real buyer questions used as a repeatable measurement instrument.
Multi-engine coverage
ChatGPT, Perplexity, Gemini, Copilot, and AI Overviews, because answers differ by engine.
Citation map
The small set of sources feeding answers in your category — the highest-leverage fix.
Accuracy check
Catches wrong pricing, features, and positioning, which are worse than absence.
Extractability findings
Direct answers, headings, tables, and schema that make content quotable.
Crawler access check
Whether GPTBot, PerplexityBot, ClaudeBot, and Google-Extended can reach you at all.
Use cases
When to reach for it
- Get a baseline for AI answer presence before investing in the channel.
- Find out what the models currently say about your pricing and features.
- Explain falling clicks against steady impressions.
- Work out why competitors are cited in your category and you are not.
- Identify the third-party sources worth correcting first.
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.