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claude-marketing-skills

Full marketing department for Claude Code—56 skills, agents, and workflows for paid media, e-commerce, SEO, content, analytics, and strategy.

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reason-machines/marketing-skills
最近来源活动
2026年5月19日 16:38
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SKILL.md
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name
claude-marketing-skills
description
Full marketing department for Claude Code—56 skills, agents, and workflows for paid media, e-commerce, SEO, content, analytics, and strategy.
triggers
["install claude marketing skills","set up marketing department for Claude","audit my Google Ads account","analyze Klaviyo email flows","optimize landing page conversion","run cross-platform ad audit","create SEO content strategy","generate schema markup for product pages"]
# claude-marketing-skills > Skill by [ara.so](https://ara.so) — Marketing Skills collection. **claude-marketing** is a collection of 56 open-source Claude Code skills, specialized agents, and autonomous workflows that give AI coding agents real marketing expertise. Each skill ships with diagnostic frameworks, industry benchmarks, audit checklists, and platform-specific reference data across paid media, SEO, e-commerce, content, CRO, analytics, and strategy. Works with Claude Code, Cursor, Aider, Windsurf, GitHub Copilot, and Gemini CLI. ## Installation ### Clone the Repository ```bash git clone https://github.com/thatrebeccarae/claude-marketing.git cd claude-marketing ``` ### Install Individual Skills Copy any skill to your Claude Code skills directory: ```bash # Example: Install Google Ads skill cp -r skills/google-ads ~/.claude/skills/ # Example: Install Klaviyo Analyst skill cp -r skills/klaviyo-analyst ~/.claude/skills/ # Example: Install AEO/GEO Optimizer cp -r skills/aeo-geo-optimizer ~/.claude/skills/ ``` ### Install Skill Packs Use setup scripts to install related skill groups: ```bash # Paid Media Pack (Google Ads, Meta, Microsoft, LinkedIn, TikTok, cross-platform) python skill-packs/scripts/setup-paid-media.py # E-commerce Pack (Shopify, Klaviyo, product feeds, conversion tracking) python skill-packs/scripts/setup-ecommerce.py # Analytics Pack (GA4, Looker Studio, GTM, data visualization) python skill-packs/scripts/setup-analytics.py # SEO Pack (Technical SEO, AEO/GEO, schema, programmatic SEO) python skill-packs/scripts/setup-seo.py # Content Pack (content creation, brand voice, social strategy) python skill-packs/scripts/setup-content.py # Strategy Pack (market research, ICP, brand DNA, pricing) python skill-packs/scripts/setup-strategy.py ``` ## Project Structure ``` claude-marketing/ ├── skills/ # 56 individual skills │ ├── google-ads/ │ │ ├── SKILL.md # Framework and decision trees │ │ ├── REFERENCE.md # Benchmarks, API schemas, rate limits │ │ └── EXAMPLES.md # Worked prompts with output │ ├── klaviyo-analyst/ │ ├── aeo-geo-optimizer/ │ └── ... ├── skill-packs/ # Grouped collections with setup wizards │ ├── paid-media/ │ ├── ecommerce/ │ ├── analytics/ │ └── scripts/ ├── agents/ # Standalone analysis agents │ ├── competitor-analyst/ │ ├── content-strategist/ │ └── paid-media-auditor/ ├── workflows/ # n8n autonomous pipelines │ └── daily-performance-digest/ └── examples/ # Cross-skill workflow walkthroughs ``` ## Skill Anatomy Each skill contains three layers: 1. **SKILL.md** — Frameworks, decision trees, diagnostic checklists 2. **REFERENCE.md** — Industry benchmarks, API schemas, rate limits, platform-specific data 3. **EXAMPLES.md** — Worked prompts with expected output ## Key Skills by Category ### Paid Media **google-ads** — Scored account audits (74 checks, A-F health grade), Quality Score optimization, Performance Max, wasted spend identification. ```bash # Install cp -r skills/google-ads ~/.claude/skills/ # Example usage # "Run a scored audit of my Google Ads account" # "Analyze Quality Score distribution and recommend optimizations" # "Find wasted spend in search campaigns" ``` **meta-ads** — Scored audits (46 checks), creative fatigue diagnosis, pixel/CAPI health, iOS 14.5+ attribution. **cross-platform-audit** — Unified multi-platform audit across Google, Meta, Microsoft with budget-weighted aggregate health score. ### E-commerce **klaviyo-analyst** (MCP-first) — Full Klaviyo audit: 4-phase account review, flow gap analysis, segment health, deliverability diagnostics. ```bash # Install cp -r skills/klaviyo-analyst ~/.claude/skills/ # Requires Klaviyo MCP server # Install: npx -y @klaviyo/mcp-server-klaviyo # Example usage # "Audit my Klaviyo flows and identify gaps" # "Analyze email deliverability and segment health" # "Generate revenue attribution report for Q1" ``` **shopify-analyst** — Store health audits, checkout optimization, product feed validation, app conflict detection. ### SEO & AI Search **aeo-geo-optimizer** — AI search optimization for ChatGPT, Perplexity, Google AI Overviews. Content scoring, citation patterns, AI crawler management. ```bash # Install cp -r skills/aeo-geo-optimizer ~/.claude/skills/ # Example usage # "Optimize this page for AI search citations" # "Audit content for ChatGPT and Perplexity visibility" # "Generate llms.txt for my documentation site" ``` **technical-seo-audit** — Deep crawl analysis, Core Web Vitals, indexation health, structured data validation. **schema-markup-generator** — JSON-LD structured data for Article, FAQ, HowTo, Product, Review, LocalBusiness. ```python # Example: Generate product schema from skills.schema_markup_generator import generate_schema product_data = { "name": "Organic Cotton T-Shirt", "description": "100% organic cotton, fair trade certified", "price": 29.99, "currency": "USD", "availability": "InStock", "brand": "EcoWear", "image": "https://example.com/images/tshirt.jpg", "sku": "ECO-TS-001", "gtin": "00012345678905" } schema_json = generate_schema("Product", product_data) print(schema_json) ``` ### Content & Strategy **brand-dna** — Extract brand identity from URL: voice, colors, typography, imagery, values → `brand-profile.json`. ```bash # Install cp -r skills/brand-dna ~/.claude/skills/ # Example usage # "Extract brand DNA from https://example.com" # "Analyze brand voice and create brand-profile.json" ``` **content-creator** — Brand voice analysis, SEO optimization, content calendar planning, multi-platform strategy. **market-research** — Consulting-grade reports (50+ pages): Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM. ### Conversion & Growth **cro-auditor** — CRO audits using LIFT model, ICE/PIE prioritization, A/B test hypothesis generation. ```bash # Install cp -r skills/cro-auditor ~/.claude/skills/ # Example usage # "Run a CRO audit on my landing page" # "Generate A/B test hypotheses prioritized by ICE score" # "Analyze form drop-off and recommend fixes" ``` **landing-page-optimizer** — Page audit: above-the-fold, value props, CTAs, social proof, mobile optimization. ## Configuration ### Environment Variables Skills that connect to external platforms require API credentials: ```bash # Google Ads export GOOGLE_ADS_DEVELOPER_TOKEN=your_dev_token export GOOGLE_ADS_CLIENT_ID=your_client_id export GOOGLE_ADS_CLIENT_SECRET=your_client_secret export GOOGLE_ADS_REFRESH_TOKEN=your_refresh_token # Meta Ads export META_ACCESS_TOKEN=your_access_token export META_AD_ACCOUNT_ID=act_1234567890 # Klaviyo export KLAVIYO_API_KEY=your_api_key export KLAVIYO_PRIVATE_KEY=your_private_key # Google Analytics 4 export GA4_PROPERTY_ID=12345678 export GA4_CREDENTIALS_PATH=/path/to/service-account.json # Shopify export SHOPIFY_STORE_URL=your-store.myshopify.com export SHOPIFY_ACCESS_TOKEN=your_access_token ``` ### MCP Server Configuration For MCP-enabled skills (Klaviyo, Google Ads, Shopify): ```json // ~/.claude/mcp_settings.json { "mcpServers": { "klaviyo": { "command": "npx", "args": ["-y", "@klaviyo/mcp-server-klaviyo"], "env": { "KLAVIYO_API_KEY": "${KLAVIYO_API_KEY}" } }, "google-ads": { "command": "npx", "args": ["-y", "@google-ads/mcp-server"], "env": { "GOOGLE_ADS_DEVELOPER_TOKEN": "${GOOGLE_ADS_DEVELOPER_TOKEN}", "GOOGLE_ADS_CLIENT_ID": "${GOOGLE_ADS_CLIENT_ID}", "GOOGLE_ADS_CLIENT_SECRET": "${GOOGLE_ADS_CLIENT_SECRET}", "GOOGLE_ADS_REFRESH_TOKEN": "${GOOGLE_ADS_REFRESH_TOKEN}" } } } } ``` ## Common Workflows ### Cross-Platform Paid Media Audit ```bash # Install required skills python skill-packs/scripts/setup-paid-media.py # Run audit # "Run a cross-platform audit of my Google Ads, Meta, and Microsoft Ads accounts" # Output: Budget-weighted aggregate health score (A-F), platform-specific recommendations ``` ### E-commerce Email Audit ```bash # Install Klaviyo skill cp -r skills/klaviyo-analyst ~/.claude/skills/ # Run audit # "Audit my Klaviyo account and identify flow gaps" # "Compare my email performance to industry benchmarks" # "Generate revenue attribution report for abandoned cart flows" ``` ### AI Search Optimization ```bash # Install AEO/GEO skill cp -r skills/aeo-geo-optimizer ~/.claude/skills/ # Optimize content # "Audit this blog post for AI search citations" # "Generate llms.txt for my developer documentation" # "Optimize product pages for ChatGPT and Perplexity visibility" ``` ### Landing Page Conversion Audit ```bash # Install CRO skills cp -r skills/cro-auditor ~/.claude/skills/ cp -r skills/landing-page-optimizer ~/.claude/skills/ # Run audit # "Run a CRO audit on https://example.com/landing-page" # "Prioritize conversion optimizations using ICE scoring" # "Generate A/B test hypotheses for the hero section" ``` ## Working with Agents Agents are standalone analysis tools that can run independently or within n8n workflows. ### Competitor Analyst Agent ```python # agents/competitor-analyst/competitor_analyst.py from competitor_analyst import CompetitorAnalyst analyst = CompetitorAnalyst() # Analyze competitor ads from public ad libraries report = analyst.analyze_competitor( competitor_domain="competitor.com", platforms=["google", "meta", "linkedin"], date_range="last_90_days" ) print(report.messaging_patterns) print(report.creative_formats) print(report.positioning_gaps) ``` ### Content Strategist Agent ```python # agents/content-strategist/content_strategist.py from content_strategist import ContentStrategist strategist = ContentStrategist() # Generate content strategy from research feed strategy = strategist.generate_strategy( topic="AI search optimization", sources=["rss_feeds", "web_scraping"], output_format="notion" ) print(strategy.content_angles) print(strategy.keyword_clusters) print(strategy.content_calendar) ``` ## Autonomous Workflows ### Daily Performance Digest (n8n) ```bash # Install workflow cp -r workflows/daily-performance-digest ~/.n8n/workflows/ # Configure in n8n: # 1. Set schedule trigger (daily at 8am) # 2. Add Slack webhook for notifications # 3. Configure platform credentials (Google Ads, Meta, GA4) # 4. Activate workflow ``` **What it does:** - Pulls performance data from Google Ads, Meta, GA4 - Runs anomaly detection on key metrics - Generates Looker Studio snapshot - Posts digest to Slack with priority alerts ## Code Examples ### Generate Schema Markup ```python from skills.schema_markup_generator import SchemaGenerator generator = SchemaGenerator() # Product schema product_schema = generator.generate( schema_type="Product", data={ "name": "Wireless Headphones", "description": "Noise-cancelling wireless headphones", "price": 199.99, "currency": "USD", "availability": "InStock", "brand": "AudioCo", "aggregateRating": { "ratingValue": 4.5, "reviewCount": 127 } } ) print(product_schema) ``` ### Run Google Ads Audit ```python from skills.google_ads import GoogleAdsAuditor auditor = GoogleAdsAuditor( developer_token=os.getenv("GOOGLE_ADS_DEVELOPER_TOKEN"), client_id=os.getenv("GOOGLE_ADS_CLIENT_ID"), client_secret=os.getenv("GOOGLE_ADS_CLIENT_SECRET"), refresh_token=os.getenv("GOOGLE_ADS_REFRESH_TOKEN") ) # Run scored audit (74 checks) audit_report = auditor.run_audit(customer_id="1234567890") print(f"Overall Health Grade: {audit_report.health_grade}") print(f"Score: {audit_report.score}/100") print("\nTop Issues:") for issue in audit_report.top_issues: print(f"- {issue.title} (Impact: {issue.impact})") ``` ### Extract Brand DNA ```python from skills.brand_dna import BrandDNAExtractor extractor = BrandDNAExtractor() # Extract from URL brand_profile = extractor.extract(url="https://example.com") # Save to JSON brand_profile.save("brand-profile.json") print(f"Brand Voice: {brand_profile.voice.tone}") print(f"Primary Colors: {brand_profile.colors.primary}") print(f"Target Audience: {brand_profile.audience.demographics}") ``` ### Optimize for AI Search ```python from skills.aeo_geo_optimizer import AEOOptimizer optimizer = AEOOptimizer() # Analyze content content = """ Your blog post or documentation content here... """ analysis = optimizer.analyze(content) print(f"AI Search Score: {analysis.score}/100")
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