Agent-Skills.md

Agent Skills: GEO — Generative Engine Optimization 2026

Use when optimizing for AI search engines (GEO) — AI Overviews, ChatGPT, Perplexity, Claude, Gemini, Copilot readiness.

UncategorizedID: fusengine/agents/seo-geo

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fusengine/agents
FusengineLicense: MIT
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pnpm dlx add-skill https://github.com/Fusengine/claude-plugins/tree/HEAD/plugins/seo/skills/seo-geo

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plugins/seo/skills/seo-geo/SKILL.md

Skill Metadata

Name
seo-geo
Description
Use when optimizing for AI search engines (GEO) — AI Overviews, ChatGPT, Perplexity, Claude, Gemini, Copilot readiness.
<objective> Covers Generative Engine Optimization (GEO) 2026 for the six target AI engines (Google AI Overviews, ChatGPT with web search, Perplexity, Claude with web search, Gemini, Bing Copilot). Documents the `scripts/geo-score.ts` LLM-readiness scoring (0-100 across 10 weighted signals), quantified impact data (statistics/authoritative citations/expert quotes boost AI visibility up to +40%; keyword stuffing costs -10%), the recommended content structure for LLM extraction, and llms.txt placement (ignored by Google's crawlers, useful for other LLMs). Distinct from seo-featured-snippets (position-0 HTML recipes) and seo-entity (the schema/salience signals that feed AI citations). </objective>

GEO — Generative Engine Optimization 2026

Target Engines

  • Google AI Overviews (formerly SGE)
  • ChatGPT with web search
  • Perplexity
  • Claude with web search
  • Gemini
  • Bing Copilot

LLM-Readiness Score (0-100)

scripts/geo-score.ts checks:

| Signal | Points | |--------|--------| | Quick answer in first 100 words | 15 | | Direct H2 questions ("What is X?") | 10 | | Tables/lists for comparable data | 10 | | Citations with dates + sources | 15 | | Statistics with attribution | 10 | | Author bio with credentials | 10 | | Schema.org markup | 10 | | Updated date < 12 months | 10 | | llms.txt present | 5 | | No JS-only content (SSR) | 5 |

Quantified Impact (Princeton / 2026 studies)

GEO techniques boost AI visibility by up to +40%. Ranked by impact:

| Technique | Visibility | |-----------|-----------| | Adding statistics | +40% | | Citing authoritative sources | +40% | | Quoting experts | +28% | | Improving text fluency | +15–30% | | Keyword stuffing | -10% (worse than baseline) |

AI Overviews cite ~13 sources on average per answer (2026); 59.6% of citations come from URLs outside the top-20 organic results.

Content Structure for LLMs

# <Topic>

**Quick answer** (40-60 words, factual, no fluff)

## What is <topic>?
Definition paragraph...

## Why does it matter?
Stats with sources...

## How to <task>?
Numbered steps...

## Comparison
| X | Y |
|---|---|

## FAQ
- Q: ...
- A: ...

llms.txt

Not required by Google (its crawlers ignore it) — useful for other LLMs, where early adopters report improved citation accuracy. Place at site root: https://example.com/llms.txt

# Site Name
> One-line description

## Pages
- [Homepage](https://example.com/): description
- [Docs](https://example.com/docs/): description

References

  • seo-entity — entity signals + schema that drive AI citations
  • skills/seo/04-geo-2026/ (ai-platforms, citation-strategies, content-structure, llm-crawlability, zero-click-optimization)
  • skills/seo/08-measurement/share-of-model.md