Master 20 SEO & GEO skills for Claude Code agents - keyword research, content optimization, technical audits, rank tracking with CORE-EEAT and CITE frameworks
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Master 20 SEO & GEO skills for Claude Code agents - keyword research, content optimization, technical audits, rank tracking with CORE-EEAT and CITE frameworks
triggers
["help me optimize content for search engines","audit this page for SEO best practices","research keywords for my content strategy","analyze competitor SEO performance","optimize content for AI citations and GEO","check technical SEO issues on my site","generate schema markup for better rankings","track keyword rankings and performance"]
seo-geo-claude-skills is a comprehensive library of 20 specialized skills that enable AI coding agents to perform Search Engine Optimization (SEO) and Generative Engine Optimization (GEO) tasks. Each skill follows a standard contract and includes built-in quality benchmarks: CORE-EEAT (80-item content quality framework) and CITE (40-item domain authority framework).
The library is organized into five phases: Research, Build, Optimize, Monitor, and Cross-cutting protocol skills. All skills work with user-provided data (Tier 1) and optionally integrate with external tools via MCP connectors.
/aaron:skillify - Review proposed skills or routes
/aaron:evolve - Controlled library changes from evidence
/aaron:guard - Maintainer validation
Skill Structure
Each skill follows this contract:
Quick Start - Immediate activation instructions
Skill Contract - Expected inputs/outputs
Handoff Summary - What to pass to next skill
Data Sources - Where data comes from (user, tools, memory)
Instructions - Step-by-step execution
Reference Materials - Supporting frameworks
Next Best Skill - Recommended workflow progression
The 20 Skills
Research Phase
keyword-research - Discover and prioritize keywords
# Natural language trigger:"Research keywords for my SaaS product targeting small teams"# Or direct command:
/aaron:discover "project management software"
competitor-analysis - Analyze competitor SEO strategies
COLD - Long-term archive (retired files, wiki history)
Wiki Layer Workflow
Phase 1 (Automatic): Index auto-refreshes at memory/wiki/index.md
Phase 2 (Manual Compilation):
# When you have ≥3 WARM files on a topic:"Compile a wiki page on our content strategy for Q1""Synthesize what we know about keyword targeting"# Handle contradictions when prompted:# (a) Accept version A# (b) Accept version B # (s) Skip/postpone# (i) Ignore permanently
Phase 3 (Retirement):
# Preview retirement candidates:
/aaron:guard --wiki --retire-preview
# After confirmation, WARM files move to memory/archive/# Recover if needed:
/aaron:remember recover wiki
# Or directly:
bash scripts/recover-retired-warm.sh
Clean restart:
rm -rf memory/wiki/ # Reverts cleanly, preserves COLD history
Quality Frameworks
CORE-EEAT (80 items)
Content quality benchmark covering:
Credibility
Originality
Relevance
Expertise
Experience
Authoritativeness
Trustworthiness
Used by: content-quality-auditor, seo-content-writer, geo-content-optimizer
CITE (40 items)
Domain authority benchmark covering:
Credibility signals
Influence metrics
Trust indicators
Expertise markers
Used by: domain-authority-auditor, backlink-analyzer
Common Workflows
Full SEO Campaign
# 1. Research
/aaron:discover "target keyword topic"
/aaron:compete https://competitor.com
/aaron:map "target keyword"# 2. Build
/aaron:brief "article topic based on research"
/aaron:write "article title from brief"
/aaron:visibility --meta --schema
# 3. Quality gate
/aaron:publish https://example.com/new-article
# 4. Optimize
/aaron:audit https://example.com/new-article
/aaron:tech https://example.com
# 5. Monitor
/aaron:watch --keywords "keyword1,keyword2,keyword3"
/aaron:report --weekly
GEO Optimization
# Optimize content for AI citations (Perplexity, ChatGPT, etc.)"Optimize this article for generative engine optimization"
/aaron:visibility --geo https://example.com/article
# Entity-first approach:"Create entity profile for [Brand/Topic]""Optimize content hub around [Entity] for AI discoverability"
Content Refresh
/aaron:refresh https://example.com/old-article
# Analyzes current performance# Suggests content updates# Identifies new keyword opportunities# Recommends internal linking improvements
