GEO: Generative Engine Optimization – Get Your Website Cited by AI Search Engines Like ChatGPT and Perplexity

GEO (Generative Engine Optimization) is an optimization solution focused on improving a website's visibility and citation rate in AI search engines like ChatGPT and Perplexity. This article will provide an in-depth analysis of GEO's 9 audit dimensions, scoring mechanism, practical applications, and related tools to help website owners adapt to content strategy shifts in the AI search era.

The core goal of traditional SEO is to improve rankings in traditional search engines like Google. However, with the rise of generative AI search tools, user search behavior has undergone fundamental changes. GEO emerged as a response; its core pursuit is "being cited"—when users ask AI questions, the AI can cite the website's content as an answer source. This is not just technical optimization but a repositioning of content strategy.

geo-skill is an open-source one-stop AI search optimization tool that supports the Claude Code plugin and mainstream AI programming tools like Cursor and Windsurf. Installation is flexible: Claude users can install it via the plugin (configure {"plugins": ["github:osvaldoabel/geo"]}), while other tools need to integrate the SKILL.md file, reflecting openness and standardized audit logic.

The GEO audit system includes 9 dimensions (total score: 100 points):

1. AI Crawler Access Permissions (10 points): Check if robots.txt allows access by GPTBot and others, and if SSR is used to avoid login walls;
2. Sitemap (5 points): Check the existence of sitemap.xml, robots references, and lastmod timestamps;
3. llms.txt File (10 points): An emerging standard, similar to robots.txt but a structured overview for AI crawlers;
4. Structured Data (20 points): Highest weight—check Schema.org tags (Organization, FAQPage, etc.) and sameAs associations;
5. Content Structure (20 points): Evaluate definitional statements, Q&A titles, and fact density;
6. Meta Tags & Social Tags (10 points): Check configurations of description tags, Open Graph, canonical, etc.;
7. Content Freshness (10 points): Check publication/modification dates, dateModified tags, and updates within the past 6 months;
8. Authority (10 points): Evaluate trust elements like About pages, author introductions, and customer reviews;
9. Content Strategy (5 points): Check blog update frequency, core topic coverage, and number of articles.

GEO scores are divided into 5 levels:

• 0-25 points (Critical): Almost invisible to AI;
• 26-50 points (Needs Work): AI may find it but not cite it;
• 51-70 points (Decent): May be cited; -71-85 points (Strong): Often cited in domain queries; -86-100 points (Elite): AI's preferred information source. Practical cases: A SaaS landing page scored 38 points (missing robots.txt, llms.txt, etc.); a software company website scored 15 points (no structured data, meta tags, etc.).

GEO-Skill output results include:

1. Terminal Report: Displays score overview, progress bar, and a table of scores for each dimension;
2. Interactive HTML Report: Donut charts, category cards, and a list of issues (grouped by severity, with repair time and priority);
3. Ready-to-Use Code: Generates complete JSON-LD, robots.txt, llms.txt, and meta tags, filled with the website's actual data.

GEO has 14 built-in Schema.org templates (covering scenarios like Organization, FAQPage, Product, etc.) and provides implementation guides for mainstream frameworks such as Next.js/React, WordPress, and Astro, as well as a general solution for static HTML.

Essential Differences Between GEO and SEO:

SEO	GEO
Pursues rankings	Pursues being cited
Optimizes keywords	Optimizes definitions and structured answers
Builds external links	Establishes entity clarity
Improves click-through rate	Becomes the answer itself
In the AI search era, uncited content is easily overlooked. It is recommended that content creators and business operators lay out GEO as early as possible to seize the high ground in AI search and become AI's preferred citation source.