GEO Analysis

GEO Analysis (Generative Engine Optimisation) measures how well your site is structured for AI crawlers, large language models, and generative search engines such as ChatGPT, Perplexity, and Google’s AI Overviews.

Why it matters

As AI-powered search becomes more prevalent, your site needs to be not just readable by humans but also easily parseable by AI agents. GEO analysis identifies structural and content issues that may prevent your site from being surfaced in AI-generated answers.

Three scores

Each page and report receives three component scores (0–100) and a weighted overall score:

Green Score — Semantic Structure

Measures how well your HTML communicates meaning:

Proper heading hierarchy (h1 → h2 → h3)
Semantic HTML elements (<article>, <section>, <main>, etc.)
Structured data (Schema.org markup)
Meta description and Open Graph tags
ARIA landmarks

Ethical Score — AI Crawlability

Measures whether your site allows and supports AI crawlers:

robots.txt configuration (no blanket AI bot blocks)
CSP restrictions that might block content access
JavaScript dependency ratio (heavily JS-rendered pages are harder to parse)
llms.txt presence (an emerging standard for AI accessibility)

Open Score — GEO Optimisation

Measures content extractability:

How well content can be parsed without JavaScript
Content structure and readability
Agent access risk assessment

In the report

GEO scores appear on both the Site Report and Page Report. The site report shows averages across all pages.

AI agent accessibility

A separate AI Agent Accessibility section on the site report shows:

Whether your site has an llms.txt file (with content preview if present)
Whether robots.txt restricts AI crawlers

Improving your GEO score

Issue	Fix
Low Green Score	Add structured data, fix heading hierarchy, add meta descriptions
Low Ethical Score	Review `robots.txt` rules, add `llms.txt`, reduce JS dependency
Low Open Score	Ensure key content is in server-rendered HTML, not JS-only