GEO-SEO Claude: get your pages quoted in AI assistant answers
GEO-SEO Claude puts generative engine optimization first and keeps classic SEO as the foundation. Running /geo audit collects up to 50 pages, then five subagents analyse citability, platforms, technical health, content and schema in parallel, and the results roll up into a composite GEO Score from 0 to 100 with a list of quick wins.
Scores passages for how readily AI systems would quote them and suggests rewrites for weak paragraphs.
Reads robots.txt, meta tags and HTTP headers to map which AI crawlers, such as GPTBot and ClaudeBot, can reach the site.
Validates an existing llms.txt or generates a new one by crawling the site.
Looks for brand mentions on platforms AI models lean on, including YouTube, Reddit, Wikipedia and LinkedIn.
Runs a CRM-lite for agencies: prospect pipeline, proposals built from audit data and monthly progress reports.
When to use it
You want to know whether AI bots can see the site at all, or if robots.txt is quietly blocking them.
An agency needs a client deliverable in Markdown or PDF with category scores and a priority list.
A month after the fixes, you have to show a client how far the GEO Score moved since the first audit.
Ask your agent
/geo quick https://example.com and give me the AI visibility snapshot.
Check which AI crawlers my robots.txt allows and propose changes.
Generate an llms.txt for our online store and explain how the file is structured.
Questions
How do I install GEO-SEO Claude?
Use npx skills add zubair-trabzada/geo-seo-claude, or clone the repository with git and run ./install.sh from its folder. On Windows the author recommends Git Bash with install-win.sh.
How is GEO different from regular SEO?
GEO aims to get pages cited by AI systems such as ChatGPT, Perplexity and Google AI Overviews. This skill keeps traditional SEO as the base but weights the score toward AI answer visibility.
What goes into the GEO Score?
Six weighted categories: AI citability and visibility 25%, brand authority 20%, content and E-E-A-T 20%, technical foundations 15%, structured data 10%, platform optimization 10%.
