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aaron-marketing-skills
Use 38 AI marketing skills for SEO/GEO optimization and influencer marketing campaigns with Claude Code integration
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Use 38 AI marketing skills for SEO/GEO optimization and influencer marketing campaigns with Claude Code integration
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | aaron-marketing-skills |
| description | Use 38 AI marketing skills for SEO/GEO optimization and influencer marketing campaigns with Claude Code integration |
| triggers | ["help me optimize SEO for my website","find influencers for my marketing campaign","analyze keyword opportunities for content","audit my page for search engine optimization","plan an influencer marketing campaign","research competitors and content gaps","generate schema markup for my content","track keyword rankings and performance"] |
Skill by ara.so — Marketing Skills collection.
Aaron Marketing Skills is a comprehensive collection of 38 marketing skills designed for AI agents (Claude Code, Cursor, etc.) covering two main disciplines: SEO/GEO (Search Engine + Generative Engine Optimization) with 20 skills, and Influencer Marketing (IMPACT) with 18 skills. The project includes 5 slash commands, three evaluation frameworks (CORE-EEAT, CITE, C³), and supports zero-dependency Markdown skill execution.
# Register the marketplace plugin
/plugin marketplace add aaron-he-zhu/aaron-marketing-skills
# Install and enable the skills
/plugin install aaron-marketing@aaron
# Install all skills
npx skills add aaron-he-zhu/aaron-marketing-skills
# Install a single skill
npx skills add aaron-he-zhu/aaron-marketing-skills -s keyword-research
git clone https://github.com/aaron-he-zhu/aaron-marketing-skills
cd aaron-marketing-skills
The project provides five main slash commands for workflow automation:
# Auto-detect intent and run appropriate workflow
/aaron-marketing:auto audit https://example.com/blog/post
# Deep/exhaustive analysis mode
/aaron-marketing:auto --deep analyze my SaaS competitor landscape
# Keyword research and competitive analysis
/aaron-marketing:research [topic/url]
# Example: Research for a specific topic
/aaron-marketing:research "project management software for remote teams"
Runs: keyword-research → competitor-analysis → serp-analysis → content-gap-analysis
# Generate content with SEO optimization
/aaron-marketing:create --brief [topic]
/aaron-marketing:create --series [topic]
/aaron-marketing:create --refresh [url]
/aaron-marketing:create --publish [content]
/aaron-marketing:create --meta [url]
/aaron-marketing:create --schema [url]
# Example: Create a content brief
/aaron-marketing:create --brief "Best practices for remote team collaboration"
# Example: Generate schema markup
/aaron-marketing:create --schema https://example.com/products/widget
# Full audit (on-page + technical + quality + authority)
/aaron-marketing:audit --full [url]
# Specific audit types
/aaron-marketing:audit --tech [url]
/aaron-marketing:audit --visibility [url]
/aaron-marketing:audit --authority [domain]
# Example: Full page audit
/aaron-marketing:audit --full https://example.com/blog/ultimate-guide
# Set up ranking alerts
/aaron-marketing:track --alert [keywords]
# Generate performance report
/aaron-marketing:track --report [timeframe]
# Store project memory
/aaron-marketing:track --remember [context]
# Example: Track keyword rankings
/aaron-marketing:track --alert "saas analytics, team dashboard, project metrics"
# keyword-research skill
# Discovers search demand, intent, and opportunity
# Natural trigger examples:
"Research keywords for my SaaS product targeting small teams"
"Find keyword opportunities in the project management niche"
# Manual invocation in Python-based hosts
from skills import run_skill
result = run_skill("keyword-research", {
"seed_keywords": ["project management", "team collaboration"],
"target_audience": "remote teams, 10-50 employees",
"intent_filter": ["informational", "commercial"]
})
# competitor-analysis skill
# Analyzes competitor content, backlinks, and rankings
result = run_skill("competitor-analysis", {
"competitors": ["asana.com", "monday.com", "clickup.com"],
"focus_urls": ["/blog", "/features"],
"metrics": ["content_gaps", "backlink_sources", "keyword_overlap"]
})
# seo-content-writer skill
# Creates optimized content following EEAT principles
result = run_skill("seo-content-writer", {
"topic": "How to improve team productivity with async communication",
"target_keywords": ["async communication", "team productivity"],
"content_type": "pillar_post",
"word_count": 2500,
"tone": "professional, helpful"
})
# schema-markup-generator skill
# Generates structured data for search engines
result = run_skill("schema-markup-generator", {
"url": "https://example.com/products/enterprise-plan",
"schema_types": ["Product", "Offer", "AggregateRating"],
"product_data": {
"name": "Enterprise Plan",
"price": "299",
"currency": "USD"
}
})
# content-quality-auditor skill
# 80-item CORE-EEAT quality gate
result = run_skill("content-quality-auditor", {
"content_url": "https://example.com/blog/guide",
"benchmark": "CORE-EEAT",
"threshold": 75 # Minimum score to pass
})
# on-page-seo-auditor skill
# Checks title, meta, headings, internal links, images
result = run_skill("on-page-seo-auditor", {
"url": "https://example.com/blog/post",
"target_keyword": "project management best practices",
"check_items": ["title", "meta_description", "h1", "keyword_density", "internal_links"]
})
# audience-analyzer skill
# Analyzes target audience demographics, psychographics, behavior
result = run_skill("audience-analyzer", {
"product": "Organic skincare line for Gen Z",
"platforms": ["TikTok", "Instagram"],
"analysis_depth": "deep" # Includes psychographics and pain points
})
# influencer-discovery skill
# Finds creators matching campaign criteria
result = run_skill("influencer-discovery", {
"niche": "sustainable fashion",
"platforms": ["Instagram", "YouTube"],
"follower_range": [10000, 100000],
"engagement_min": 3.5,
"location": "US, UK, Canada"
})
# fit-scorer skill
# Scores influencers on C³ ACE framework (Audience, Content, Engagement)
result = run_skill("fit-scorer", {
"influencers": ["@creator1", "@creator2"],
"campaign_brief": {
"product": "eco-friendly water bottle",
"target_age": "18-35",
"values": ["sustainability", "active lifestyle"]
},
"framework": "C3_ACE"
})
# campaign-planner skill
# Creates end-to-end influencer campaign strategy
result = run_skill("campaign-planner", {
"goal": "Launch new product line with 50K reach",
"budget": 15000,
"duration": "60 days",
"platforms": ["Instagram", "TikTok"],
"deliverables": ["feed_posts", "stories", "reels"]
})
# brief-generator skill
# Generates creator briefs with guidelines and requirements
result = run_skill("brief-generator", {
"campaign_id": "summer_launch_2024",
"creator_tier": "micro",
"content_type": "Instagram Reel",
"key_messages": ["sustainability", "convenience", "style"],
"compliance": ["FTC_disclosure", "brand_safety"]
})
# outreach-manager skill
# Manages influencer outreach sequences
result = run_skill("outreach-manager", {
"influencer_list": ["creator1@email.com", "creator2@email.com"],
"template": "collaboration_invite",
"personalization": {
"creator1@email.com": {"recent_post": "Your reel about sustainable living"}
},
"follow_up_days": [3, 7]
})
# performance-analyzer skill
# Tracks campaign metrics across platforms
result = run_skill("performance-analyzer", {
"campaign_id": "summer_launch_2024",
"metrics": ["reach", "engagement_rate", "conversions", "ROI"],
"breakdown": ["by_creator", "by_platform", "by_content_type"]
})
# roi-calculator skill
# Calculates influencer marketing ROI
result = run_skill("roi-calculator", {
"campaign_spend": 15000,
"revenue_generated": 47500,
"attribution_model": "last_click",
"include_metrics": ["CPM", "CPC", "CPA", "ROAS"]
})
Four skills form the protocol layer across all marketing activities:
# content-quality-auditor
# 80-item CORE-EEAT benchmark
result = run_skill("content-quality-auditor", {
"content_url": "https://example.com/article",
"audit_type": "CORE-EEAT",
"output_format": "scorecard"
})
# domain-authority-auditor
# 40-item CITE trust benchmark
result = run_skill("domain-authority-auditor", {
"domain": "example.com",
"audit_type": "CITE",
"compare_to": ["competitor1.com", "competitor2.com"]
})
# entity-optimizer
# Manages canonical entity profiles (brand, author, organization)
result = run_skill("entity-optimizer", {
"entity_type": "Organization",
"entity_name": "Acme Corp",
"attributes": {
"sameAs": ["https://twitter.com/acmecorp", "https://linkedin.com/company/acme"],
"expertise": ["B2B SaaS", "Project Management"]
}
})
# memory-management
# HOT/WARM/COLD project memory storage
result = run_skill("memory-management", {
"action": "capture",
"tier": "HOT",
"context": {
"project": "Q4_content_campaign",
"data": {"keywords": [...], "competitors": [...]}
}
})
Skills use environment variables for optional tool connectors:
# API keys for enhanced data sources (Tier 2+ connectors)
export SERP_API_KEY="your_serpapi_key"
export AHREFS_API_KEY="your_ahrefs_key"
export SEMRUSH_API_KEY="your_semrush_key"
# Social platform APIs for influencer data
export INSTAGRAM_ACCESS_TOKEN="your_instagram_token"
export TIKTOK_API_KEY="your_tiktok_key"
export YOUTUBE_API_KEY="your_youtube_key"
# Analytics integration
export GOOGLE_ANALYTICS_CREDENTIALS="path/to/credentials.json"
Important: All skills work at Tier 1 (user-provided data) without any API keys. Connectors enhance automation but are optional.
# Step 1: Research keywords
keywords = run_skill("keyword-research", {
"seed": ["project management software"]
})
# Step 2: Analyze competitors
competitors = run_skill("competitor-analysis", {
"keywords": keywords["top_keywords"]
})
# Step 3: Find content gaps
gaps = run_skill("content-gap-analysis", {
"your_domain": "example.com",
"competitors": competitors["top_competitors"]
})
# Step 4: Create optimized content
content = run_skill("seo-content-writer", {
"topic": gaps["priority_topics"][0],
"target_keywords": gaps["opportunity_keywords"]
})
# Step 5: Run quality audit (80-item CORE-EEAT)
audit = run_skill("content-quality-auditor", {
"content": content["draft"],
"benchmark": "CORE-EEAT",
"threshold": 75
})
# Step 6: Generate schema markup
schema = run_skill("schema-markup-generator", {
"content": content["final"],
"schema_types": ["Article", "FAQPage"]
})
# Step 1: Analyze target audience
audience = run_skill("audience-analyzer", {
"product": "Sustainable fashion brand",
"platforms": ["Instagram", "TikTok"]
})
# Step 2: Discover influencers
creators = run_skill("influencer-discovery", {
"niche": "sustainable fashion",
"audience_match": audience["demographics"],
"follower_range": [10000, 100000]
})
# Step 3: Score creator fit (C³ ACE framework)
scored = run_skill("fit-scorer", {
"influencers": creators["matches"],
"campaign_criteria": audience["psychographics"],
"framework": "C3_ACE"
})
# Step 4: Plan campaign
campaign = run_skill("campaign-planner", {
"selected_creators": scored["top_10"],
"budget": 20000,
"goal": "brand_awareness"
})
# Step 5: Generate creator briefs
briefs = run_skill("brief-generator", {
"campaign": campaign["plan"],
"per_creator": True,
"include_compliance": ["FTC_disclosure"]
})
# Step 6: Track performance
performance = run_skill("performance-analyzer", {
"campaign_id": campaign["id"],
"metrics": ["reach", "engagement", "conversions"]
})
# Capture research in HOT memory
run_skill("memory-management", {
"action": "capture",
"tier": "HOT",
"context": {
"project": "Q1_SEO_Campaign",
"phase": "research",
"data": {
"keywords": [...],
"competitors": [...]
}
}
})
# Later: Query memory for context
memory = run_skill("memory-management", {
"action": "query",
"project": "Q1_SEO_Campaign",
"phase": "research"
})
# Promote important items to WARM for long-term retention
run_skill("memory-management", {
"action": "promote",
"from_tier": "HOT",
"to_tier": "WARM",
"filter": {"importance": "high"}
})
# Run comprehensive content quality audit
audit = run_skill("content-quality-auditor", {
"content_url": "https://example.com/article",
"framework": "CORE-EEAT",
"categories": [
"Core_Content", # 20 items
"Originality", # 15 items
"Relevance", # 15 items
"Expertise", # 10 items
"Experience", # 10 items
"Authoritativeness", # 5 items
"Trustworthiness" # 5 items
],
"pass_threshold": 75
})
# Output includes per-category scores, blockers, and recommendations
# Audit domain trust signals
domain_audit = run_skill("domain-authority-auditor", {
"domain": "example.com",
"framework": "CITE",
"categories": [
"Credibility", # 10 items - author expertise, citations
"Infrastructure", # 10 items - technical health, security
"Transparency", # 10 items - about pages, contact info
"Engagement" # 10 items - social proof, user signals
],
"compare_to": ["competitor.com"]
})
# Score influencer fit using C³ framework
c3_score = run_skill("fit-scorer", {
"influencer": "@creator_handle",
"framework": "C3",
"dimensions": {
"ACE": { # Creator fit
"Audience_alignment": True,
"Content_quality": True,
"Engagement_authenticity": True
},
"ART": { # Content quality
"Authenticity": True,
"Relevance": True,
"Technique": True
},
"ROI": { # Campaign performance
"Reach": True,
"Outcomes": True,
"Investment_efficiency": True
}
}
})
# Verify plugin is registered
/plugin list
# Re-install if needed
/plugin uninstall aaron-marketing@aaron
/plugin install aaron-marketing@aaron
# Check marketplace registration
/plugin marketplace list
# Ensure you're using the new namespace
# Old: /seo:audit or /aaron-seo-geo:audit
# New: /aaron-marketing:audit
# The auto command can recover old syntax
/aaron-marketing:auto /seo:audit https://example.com
# Most skills work at Tier 1 (user-provided data)
# If you need automated data fetching, configure connectors:
export SERP_API_KEY="your_key"
export AHREFS_API_KEY="your_key"
# Check CONNECTORS.md for tier documentation
# Verify memory tier and project name
result = run_skill("memory-management", {
"action": "query",
"tier": "HOT", # Try "WARM" or "COLD" if not in HOT
"project": "exact_project_name" # Case-sensitive
})
# List all stored memory contexts
result = run_skill("memory-management", {
"action": "list",
"tier": "all"
})
# Review detailed breakdown
audit = run_skill("content-quality-auditor", {
"content_url": "url",
"framework": "CORE-EEAT",
"verbose": True # Shows per-item scores and failures
})
# Focus on blockers first (items scoring < 2)
blockers = audit["blockers"]
# Use content-refresher skill to address specific issues
refreshed = run_skill("content-refresher", {
"url": "url",
"focus_areas": blockers["categories"]
})
# Widen search criteria
result = run_skill("influencer-discovery", {
"niche": "broader_category",
"follower_range": [5000, 500000], # Wider range
"engagement_min": 2.0, # Lower threshold
"location": "any" # Remove geo restrictions
})
# Try alternative platforms
result = run_skill("influencer-discovery", {
"platforms": ["Instagram", "YouTube", "TikTok"], # Expand platforms
"niche": "related_niche"
})
Create Python scripts to chain skills:
#!/usr/bin/env python3
# custom_seo_workflow.py
from skills import run_skill
def full_seo_workflow(topic, domain):
"""Complete SEO workflow from research to publish."""
# Research
kw = run_skill("keyword-research", {"seed": [topic]})
comp = run_skill("competitor-analysis", {"keywords": kw["top_keywords"]})
gaps = run_skill("content-gap-analysis", {
"your_domain": domain,
"competitors": comp["domains"]
})
# Create
content = run_skill("seo-content-writer", {
"topic": gaps["priority_topics"][0],
"keywords": gaps["opportunity_keywords"]
})
# Quality gate
audit = run_skill("content-quality-auditor", {
"content": content["draft"],
"threshold": 75
})
if audit["score"] < 75:
# Refresh until passing
content = run_skill("content-refresher", {
"content": content["draft"],
"focus": audit["low_scoring_areas"]
})
# Optimize
meta = run_skill("meta-tags-optimizer", {"content": content["final"]})
schema = run_skill("schema-markup-generator", {"content": content["final"]})
return {
"content": content["final"],
"meta": meta,
"schema": schema,
"quality_score": audit["score"]
}
# Run workflow
result = full_seo_workflow("remote work tools", "example.com")
print(result)
Commands in commands/ are Bash scripts calling skill runners:
#!/usr/bin/env bash
# commands/aaron-marketing-audit.sh
# Full audit mode
if [[ "$1" == "--full" ]]; then
URL="$2"
# On-page audit
./skills/optimize/on-page-seo-auditor/run.sh "$URL"
# Quality audit (CORE-EEAT)
./skills/cross-cutting/content-quality-auditor/run.sh "$URL" --framework CORE-EEAT
# Technical audit
./skills/optimize/technical-seo-checker/run.sh "$URL"
# Domain authority (CITE)
DOMAIN=$(echo "$URL" | awk -F/ '{print $3}')
./skills/cross-cutting/domain-authority-auditor/run.sh "$DOMAIN" --framework CITE
fi
references/core-eeat-benchmark.md — 80-item content quality frameworkreferences/cite-domain-rating.md — 40-item domain authority frameworkreferences/c3-benchmark.md — Influencer scoring (ACE/ART/ROI)references/skill-contract.md — Standard skill structurereferences/state-model.md — Memory tier semanticsCONNECTORS.md — Optional API integration tiersApache License 2.0 — See LICENSE
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