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Seo geo

Skill aAAaqwq/AGI-Super-Team/skills/seo-geo

SEO & GEO (Generative Engine Optimization) for websites. Analyze keywords, generate schema markup, optimize for AI search engines (ChatGPT, Perplexity, Gemini, Copilot, Claude) and traditional search (Google, Bing). Use when user wants to improve search visibility, search optimization, search ranking, AI visibility, ChatGPT ranking, Google AI Overview, indexing, JSON-LD, meta tags, or keyword research.From its SKILL.md

Install
npx -y skills add aAAaqwq/AGI-Super-Team --skill seo-geo

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

8.2 KB, ~2.0k tokens by cl100k_base, as published. Nobody here has run it

SEO/GEO Optimization Skill

Comprehensive SEO and GEO (Generative Engine Optimization) for websites. Optimize for both traditional search engines (Google, Bing) and AI search engines (ChatGPT, Perplexity, Gemini, Copilot, Claude).

Quick Reference

GEO = Generative Engine Optimization - Optimizing content to be cited by AI search engines.

Key Insight: AI search engines don't rank pages - they cite sources. Being cited is the new "ranking #1".

Workflow

Step 1: Website Audit

Get the target URL and analyze current SEO/GEO status.

Basic SEO Audit (Free):

python3 scripts/seo_audit.py "https://example.com"

Use this for: Quick technical SEO check (title, meta, H1, robots, sitemap, load time). No API needed.


Check Meta Tags:

curl -sL "https://example.com" | grep -E "<title>|<meta name=\"description\"|<meta property=\"og:|application/ld\+json" | head -20

Use this for: Quick check of essential meta tags and schema markup on any webpage.


Check robots.txt:

curl -s "https://example.com/robots.txt"

Use this for: Verify which bots are allowed/blocked. Critical for ensuring AI search engines can crawl your site.


Check sitemap:

curl -s "https://example.com/sitemap.xml" | head -50

Use this for: Verify sitemap structure and ensure all important pages are included for search engine discovery.

Verify AI Bot Access:

# These bots should be allowed in robots.txt:
- Googlebot (Google)
- Bingbot (Bing/Copilot)
- PerplexityBot (Perplexity)
- ChatGPT-User (ChatGPT with browsing)
- ClaudeBot / anthropic-ai (Claude)
- GPTBot (OpenAI)

Step 2: Keyword Research

Use WebSearch to research target keywords:

WebSearch: "{keyword} keyword difficulty site:ahrefs.com OR site:semrush.com"
WebSearch: "{keyword} search volume 2026"
WebSearch: "site:{competitor.com} {keyword}"

Analyze:

  • Search volume and difficulty
  • Competitor keyword strategies
  • Long-tail keyword opportunities
  • International keyword conflicts (e.g., "OPC" = industrial automation in English markets)

Step 3: GEO Optimization (AI Search Engines)

Apply the 9 Princeton GEO Methods (see references/geo-research.md):

MethodVisibility BoostHow to Apply
Cite Sources+40%Add authoritative citations and references
Statistics Addition+37%Include specific numbers and data points
Quotation Addition+30%Add expert quotes with attribution
Authoritative Tone+25%Use confident, expert language
Easy-to-understand+20%Simplify complex concepts
Technical Terms+18%Include domain-specific terminology
Unique Words+15%Increase vocabulary diversity
Fluency Optimization+15-30%Improve readability and flow
Keyword Stuffing-10%AVOID - hurts visibility

Best Combination: Fluency + Statistics = Maximum boost

Generate FAQPage Schema (+40% AI visibility):

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [{
    "@type": "Question",
    "name": "What is [topic]?",
    "acceptedAnswer": {
      "@type": "Answer",
      "text": "According to [source], [answer with statistics]."
    }
  }]
}

Optimize Content Structure:

  • Use "answer-first" format (direct answer at top)
  • Clear H1 > H2 > H3 hierarchy
  • Bullet points and numbered lists
  • Tables for comparison data
  • Short paragraphs (2-3 sentences max)

Step 4: Traditional SEO Optimization

Meta Tags Template:

<title>{Primary Keyword} - {Brand} | {Secondary Keyword}</title>
<meta name="description" content="{Compelling description with keyword, 150-160 chars}">
<meta name="keywords" content="{keyword1}, {keyword2}, {keyword3}">

<!-- Open Graph -->
<meta property="og:title" content="{Title}">
<meta property="og:description" content="{Description}">
<meta property="og:image" content="{Image URL 1200x630}">
<meta property="og:url" content="{Canonical URL}">
<meta property="og:type" content="website">

<!-- Twitter Cards -->
<meta name="twitter:card" content="summary_large_image">
<meta name="twitter:title" content="{Title}">
<meta name="twitter:description" content="{Description}">
<meta name="twitter:image" content="{Image URL}">

JSON-LD Schema (see references/schema-templates.md):

  • WebPage / Article for content pages
  • FAQPage for FAQ sections
  • Product for product pages
  • Organization for about pages
  • SoftwareApplication for tools/apps

Check Content:

  • H1 contains primary keyword
  • Images have descriptive alt text
  • Internal links to related content
  • External links have rel="noopener noreferrer"
  • Content is mobile-friendly
  • Page loads in < 3 seconds

Step 5: Validate & Monitor

Schema Validation:

# Open Google Rich Results Test
open "https://search.google.com/test/rich-results?url={encoded_url}"

# Open Schema.org Validator
open "https://validator.schema.org/?url={encoded_url}"

Check Indexing Status:

# Google (use Search Console API or manual check)
open "https://www.google.com/search?q=site:{domain}"

# Bing
open "https://www.bing.com/search?q=site:{domain}"

Generate Report:

## SEO/GEO Optimization Report

### Current Status
- Meta Tags: ✅/❌
- Schema Markup: ✅/❌
- AI Bot Access: ✅/❌
- Mobile Friendly: ✅/❌
- Page Speed: X seconds

### Recommendations
1. [Priority 1 action]
2. [Priority 2 action]
3. [Priority 3 action]

### GEO Optimizations Applied
- [ ] FAQPage schema added
- [ ] Statistics included
- [ ] Citations added
- [ ] Answer-first structure

Platform-Specific Optimization

See references/platform-algorithms.md for detailed ranking factors.

ChatGPT

  • Focus on branded domain authority (cited 11% more than third-party)
  • Update content within 30 days (3.2x more citations)
  • Build backlinks (>350K referring domains = 8.4 avg citations)
  • Match content style to ChatGPT's response format

Perplexity

  • Allow PerplexityBot in robots.txt
  • Use FAQ Schema (higher citation rate)
  • Host PDF documents (prioritized for citation)
  • Focus on semantic relevance over keywords

Google AI Overview (SGE)

  • Optimize for E-E-A-T (Experience, Expertise, Authority, Trust)
  • Use structured data (Schema markup)
  • Build topical authority (content clusters + internal linking)
  • Include authoritative citations (+132% visibility)

Microsoft Copilot / Bing

  • Ensure Bing indexing (required for citation)
  • Optimize for Microsoft ecosystem (LinkedIn, GitHub mentions help)
  • Page speed < 2 seconds
  • Clear entity definitions

Claude AI

  • Ensure Brave Search indexing (Claude uses Brave, not Google)
  • High factual density (data-rich content preferred)
  • Clear structural clarity (easy to extract)

Skill Dependencies

This skill works best with:

  • twitter skill - Search SEO experts for latest tips
  • reddit skill - Search r/SEO, r/bigseo for discussions
  • WebSearch - Keyword research and competitor analysis

References

What ships with it: 26 files

134.7 KB alongside SKILL.md, 12 of them executable

Gives 0 of the 12 instructions most research analysis skills give in ~2.0k tokens

Counted across 1,213 of the 2,113 authors here whose files we hold, read 2026-09-06

  • Cite sources for every important claimin 47 of 1213, across 38 files
  • Separate facts from inferences and recommendationsin 21 of 1213, across 12 files
  • Write findings to a markdown filein 19 of 1213
  • Label every insight with a confidence levelin 18 of 1213, across 8 files
  • Read product marketing context before asking questionsin 18 of 1213, across 8 files
  • Rank themes by frequency and intensityin 16 of 1213, across 6 files
  • Establish research mode before proceedingin 16 of 1213, across 6 files
  • Segment survey responses by customer tier or tenurein 16 of 1213, across 6 files
  • Categorize support tickets before analyzingin 16 of 1213, across 6 files
  • Weight research sources from the last twelve monthsin 16 of 1213, across 6 files
  • Use at least five data points per segmentin 15 of 1213, across 5 files
  • Extract verbatim quotes for all research findingsin 15 of 1213, across 5 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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