AI Marketing Skills

Open-source Claude Code skills for marketing and sales teams. Built by the team at Single Brain — battle-tested on real pipelines generating millions in revenue.

These aren't prompts. They're complete workflows — scripts, scoring algorithms, expert panels, and automation pipelines you can plug into Claude Code (or any AI coding agent) and run today.

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🗂️ Skills

Category	What It Does	Key Skills
Growth Engine	Autonomous marketing experiments that run, measure, and optimize themselves	Experiment Engine, Pacing Alerts, Weekly Scorecard
Sales Pipeline	Turn anonymous website visitors into qualified pipeline	RB2B Router, Deal Resurrector, Trigger Prospector, ICP Learner
Content Ops	Ship content that scores 90+ every time	Expert Panel, Quality Gate, Editorial Brain, Quote Miner
Outbound Engine	ICP definition to emails in inbox — fully automated	Cold Outbound Optimizer, Lead Pipeline, Competitive Monitor
SEO Ops	Find the keywords your competitors missed	Content Attack Briefs, GSC Optimizer, Trend Scout
Finance Ops	Your AI CFO that finds hidden costs in 30 minutes	CFO Briefing, Cost Estimate, Scenario Modeler
Revenue Intelligence	Prove content ROI and turn sales calls into strategy	Gong Insight Pipeline, Revenue Attribution, Client Report Generator
Conversion Ops	Score any landing page and turn survey data into lead magnets	CRO Audit, Survey-to-Lead-Magnet Engine
Podcast Ops	One episode → 20+ content pieces across every platform	Podcast-to-Everything Pipeline, Content Calendar
Team Ops	Ruthless performance audits and meeting intelligence	Elon Algorithm, Meeting-to-Action Extractor
Sales Playbook	Value-based pricing framework that turns $10K deals into $100K deals	Pre-Call Briefing, Tiered Packager, Call Analyzer, Pattern Library

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🚀 Quick Start

Each skill category has its own README with setup instructions. The general pattern:

# 1. Clone the repo
git clone https://github.com/singlegrain/ai-marketing-skills.git
cd ai-marketing-skills

# 2. Pick a category
cd growth-engine  # or sales-pipeline, content-ops, etc.

# 3. Install dependencies
pip install -r requirements.txt

# 4. Set up environment variables
cp .env.example .env
# Edit .env with your API keys

# 5. Run
python experiment-engine.py create \
  --hypothesis "Thread posts get 2x engagement vs single posts" \
  --variable format \
  --variants '["thread", "single"]' \
  --metric impressions

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🧠 How These Work with Claude Code

Every category includes a SKILL.md file. Drop it into your Claude Code project and the AI agent knows how to use the tools:

# In your project directory
cp ai-marketing-skills/growth-engine/SKILL.md .claude/skills/growth-engine.md

Then ask Claude Code: "Run an experiment testing carousel vs. static posts on LinkedIn" — it handles the rest.

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📊 What Makes These Different

These aren't toy demos. Each skill was built to run real business operations:

• Growth Engine uses bootstrap confidence intervals and Mann-Whitney U tests — real statistics, not vibes
• Deal Resurrector has three intelligence layers including "follow the champion" — tracking departed contacts to their new companies
• ICP Learner rewrites your ideal customer profile based on actual win/loss data — your targeting improves automatically
• Expert Panel recursively scores content with domain-specific expert personas until quality hits 90+
• RB2B Router does intent scoring, seniority-based company dedup, and agency classification before routing to outbound sequences

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📁 Repository Structure

ai-marketing-skills/
├── README.md              ← You are here
├── growth-engine/         ← Autonomous experiments
│   ├── SKILL.md
│   ├── experiment-engine.py
│   ├── pacing-alert.py
│   ├── autogrowth-weekly-scorecard.py
│   └── ...
├── sales-pipeline/        ← Visitor → pipeline automation
│   ├── SKILL.md
│   ├── rb2b_instantly_router.py
│   ├── deal_resurrector.py
│   ├── trigger_prospector.py
│   ├── icp_learning_analyzer.py
│   └── ...
├── content-ops/           ← Quality scoring & production
│   ├── SKILL.md
│   ├── scripts/
│   ├── experts/           ← 9 expert panel definitions
│   ├── scoring-rubrics/   ← 5 scoring rubric templates
│   └── ...
├── outbound-engine/       ← Cold outbound automation
│   ├── SKILL.md
│   ├── scripts/
│   ├── references/        ← ICP template, copy rules
│   └── ...
├── seo-ops/               ← SEO intelligence
│   ├── SKILL.md
│   ├── content_attack_brief.py
│   ├── gsc_client.py
│   ├── trend_scout.py
│   └── ...
├── finance-ops/           ← Financial analysis
│   ├── SKILL.md
│   ├── scripts/
│   ├── references/        ← Metrics, rates, ROI models
│   └── ...
├── revenue-intelligence/  ← Sales call insights + attribution
│   ├── SKILL.md
│   ├── gong_insight_pipeline.py
│   ├── revenue_attribution.py
│   └── client_report_generator.py
├── conversion-ops/        ← CRO + lead magnet generation
│   ├── SKILL.md
│   ├── cro_audit.py
│   └── survey_lead_magnet.py
├── podcast-ops/           ← Podcast → content factory
│   ├── SKILL.md
│   └── podcast_pipeline.py
├── team-ops/              ← Performance audits + meeting intel
│   ├── SKILL.md
│   ├── team_performance_audit.py
│   └── meeting_action_extractor.py
└── sales-playbook/        ← Value-based pricing framework
    ├── SKILL.md
    ├── value_pricing_briefing.py
    ├── value_pricing_packager.py
    ├── call_analyzer.py
    └── pricing_pattern_library.py

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🔒 Privacy & Security

Every skill is built with data privacy in mind:

• PII Sanitizer scans code and data for sensitive information before commits (security/sanitizer.py)
• Pre-commit hook blocks commits containing detected PII patterns
• Configurable blocklists for company names, person names, and custom patterns
• See security/README.md for setup

# Scan for sensitive data
python3 security/sanitizer.py --scan --dir . --recursive

# Install the pre-commit hook
cp security/pre-commit-hook.sh .git/hooks/pre-commit && chmod +x .git/hooks/pre-commit

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📡 Telemetry (Opt-In)

Anonymous usage telemetry helps us understand which skills people actually use. Fully opt-in, privacy-first:

• Local logging always — see your own usage stats in ~/.ai-marketing-skills/analytics/
• Remote reporting optional — only if you explicitly opt in on first run
• Data collected: skill name, duration, success/fail, version, OS. Nothing else. No code, no file paths, no repo content.
• Version checks — get notified when new skills are available

# View your local usage stats
python3 telemetry/telemetry_report.py

# Check for updates
python3 telemetry/version_check.py

See telemetry/README.md for details.

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🤝 Contributing

Found a bug? Have an improvement? PRs welcome. Read CONTRIBUTING.md for guidelines.

1. Fork the repo
2. Create your feature branch (git checkout -b feature/better-scoring)
3. Run python3 security/sanitizer.py --scan before committing
4. Commit your changes
5. Push to the branch
6. Open a Pull Request

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📄 License

MIT License. Use these however you want.

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Star this repo if you find it useful. It helps others discover these tools.

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