Optimizes content for AI search engines using GEO scoring and LLM-readiness signals.
npx skills add https://github.com/fusengine/kimi-code --skill seo-geo-fusengine
Please help me install this Agent Skill. Skill: seo-geo Source: https://github.com/fusengine/kimi-code/tree/main/plugins/seo/skills/seo-geo Command: npx skills add https://github.com/fusengine/kimi-code --skill seo-geo-fusengine
scripts/geo-score.ts to score pages 0-100 across 10 weighted signals including quick answers, citations, statistics, schema markup, and llms.txt. - Quantified GEO Guidance: Applies research-backed impact data showing statistics and authoritative citations raise AI visibility up to +40% while keyword stuffing costs -10%. - Content Structure Templates: Provides a recommended Markdown structure (quick answer, definitional H2s, comparison tables, FAQ) designed for LLM extraction across six target engines. - Use Case: A content team auditing a blog post can score its AI readiness, restructure it with direct-question headings and sourced statistics, and add an llms.txt file to improve citation rates in Perplexity and ChatGPT answers. ## Quick Start Use the seo-geo skill to score my article's AI search readiness and restructure it for citation by ChatGPT and Perplexity.High-intent search queries and answers about installing and using this skill.
Generative Engine Optimization focuses on adding statistics with attribution, citing authoritative sources, quoting experts, and structuring content with quick answers and direct-question headings. These techniques can raise AI visibility by up to +40% according to Princeton research.
The geo-score.ts script rates LLM readiness from 0-100 across 10 weighted signals. The highest-value signals are a quick answer in the first 100 words and citations with dates and sources, each worth 15 points.
No, Google's crawlers ignore llms.txt, so it does not affect AI Overviews. It is still useful for other LLMs, where early adopters report improved citation accuracy when the file is placed at the site root.
No, keyword stuffing reduces AI visibility by about 10%, performing worse than baseline. AI engines reward fluency, statistics, and authoritative citations instead of keyword density.
Start with a 40-60 word factual quick answer, then use definitional H2 questions, numbered how-to steps, comparison tables, and an FAQ section. This structure maps to how AI engines extract and cite passages.
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