Optimize site-wide content for AI search extraction, citations, and llms.txt metadata.
npx skills add https://github.com/rampstackco/claude-skills --skill seo-aeo-geo
Please help me install this Agent Skill. Skill: seo-aeo-geo Source: https://github.com/rampstackco/claude-skills/tree/main/skills/seo-aeo-geo Command: npx skills add https://github.com/rampstackco/claude-skills --skill seo-aeo-geo
AI-driven search experiences often struggle when content is hard to extract, poorly structured, or lacking robust citations. This skill provides a disciplined framework to optimize for AI overviews and citation-ready signals, helping content be found and trusted by AI agents.
Provide an AI-ready content optimization brief to apply AEO and GEO signals across a page.
High-intent search queries and answers about installing and using this skill.
To optimize content for AI search overviews, you design pages with extractable structures, question-led headings, and authoritative citations. This makes information easily parsable and trusted by AI search experiences.
llms.txt is a concise metadata guide that steers AI context and citation behavior. Creating and maintaining it improves AI search visibility by explicitly signaling which content to extract and reference.
You make website content extractable by applying modular data structures and question-led headings across site templates. This optimization ensures AI agents can easily parse and reference your information.
AI search engines look for authoritative signals like embedded references, methodology disclosures, and dates. Adding these citations to your content improves AI trust and increases the likelihood of being referenced.
Yes, you can apply AEO and GEO optimization signals to existing site templates. The framework provides an optimization brief to update site-wide content and pages for AI discovery and citation readiness.
Content fails to appear in AI-driven search results when it lacks extractable structure, robust citations, or llms.txt alignment. Poorly structured information prevents AI agents from parsing and trusting the page.
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