a96d0d8889
- growth-engine: Autonomous experiment engine (Karpathy autoresearch for marketing) - sales-pipeline: RB2B router, deal resurrector, trigger prospector, ICP learner - content-ops: Expert panel, quality gate, editorial brain, quote miner - outbound-engine: Cold outbound optimizer, lead pipeline, competitive monitor - seo-ops: Content attack briefs, GSC optimizer, trend scout - finance-ops: CFO briefing, cost estimate, scenario modeler 79 files, all sanitized - zero hardcoded credentials or internal references.
146 lines
5.3 KiB
Markdown
146 lines
5.3 KiB
Markdown
# AI Marketing Skills
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**Open-source Claude Code skills for B2B marketing and sales teams.** Built by the team at [Single Grain](https://www.singlegrain.com) — battle-tested on real pipelines generating millions in revenue.
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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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---
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## 🗂️ Skills
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| Category | What It Does | Key Skills |
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|----------|-------------|------------|
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| [**Growth Engine**](./growth-engine/) | Autonomous marketing experiments that run, measure, and optimize themselves | Experiment Engine, Pacing Alerts, Weekly Scorecard |
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| [**Sales Pipeline**](./sales-pipeline/) | Turn anonymous website visitors into qualified pipeline | RB2B Router, Deal Resurrector, Trigger Prospector, ICP Learner |
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| [**Content Ops**](./content-ops/) | Ship content that scores 90+ every time | Expert Panel, Quality Gate, Editorial Brain, Quote Miner |
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| [**Outbound Engine**](./outbound-engine/) | ICP definition to emails in inbox — fully automated | Cold Outbound Optimizer, Lead Pipeline, Competitive Monitor |
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| [**SEO Ops**](./seo-ops/) | Find the keywords your competitors missed | Content Attack Briefs, GSC Optimizer, Trend Scout |
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| [**Finance Ops**](./finance-ops/) | Your AI CFO that finds hidden costs in 30 minutes | CFO Briefing, Cost Estimate, Scenario Modeler |
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---
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## 🚀 Quick Start
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Each skill category has its own README with setup instructions. The general pattern:
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```bash
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# 1. Clone the repo
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git clone https://github.com/singlegrain/ai-marketing-skills.git
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cd ai-marketing-skills
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# 2. Pick a category
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cd growth-engine # or sales-pipeline, content-ops, etc.
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# 3. Install dependencies
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pip install -r requirements.txt
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# 4. Set up environment variables
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cp .env.example .env
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# Edit .env with your API keys
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# 5. Run
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python experiment-engine.py create \
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--hypothesis "Thread posts get 2x engagement vs single posts" \
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--variable format \
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--variants '["thread", "single"]' \
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--metric impressions
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```
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---
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## 🧠 How These Work with Claude Code
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Every category includes a `SKILL.md` file. Drop it into your Claude Code project and the AI agent knows how to use the tools:
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```
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# In your project directory
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cp ai-marketing-skills/growth-engine/SKILL.md .claude/skills/growth-engine.md
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```
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Then ask Claude Code: *"Run an experiment testing carousel vs. static posts on LinkedIn"* — it handles the rest.
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---
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## 📊 What Makes These Different
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**These aren't toy demos.** Each skill was built to run real business operations:
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- **Growth Engine** uses bootstrap confidence intervals and Mann-Whitney U tests — real statistics, not vibes
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- **Deal Resurrector** has three intelligence layers including "follow the champion" — tracking departed contacts to their new companies
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- **ICP Learner** rewrites your ideal customer profile based on actual win/loss data — your targeting improves automatically
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- **Expert Panel** recursively scores content with domain-specific expert personas until quality hits 90+
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- **RB2B Router** does intent scoring, seniority-based company dedup, and agency classification before routing to outbound sequences
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---
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## 📁 Repository Structure
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```
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ai-marketing-skills/
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├── README.md ← You are here
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├── growth-engine/ ← Autonomous experiments
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│ ├── SKILL.md
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│ ├── experiment-engine.py
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│ ├── pacing-alert.py
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│ ├── autogrowth-weekly-scorecard.py
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│ └── ...
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├── sales-pipeline/ ← Visitor → pipeline automation
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│ ├── SKILL.md
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│ ├── rb2b_instantly_router.py
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│ ├── deal_resurrector.py
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│ ├── trigger_prospector.py
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│ ├── icp_learning_analyzer.py
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│ └── ...
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├── content-ops/ ← Quality scoring & production
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│ ├── SKILL.md
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│ ├── scripts/
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│ ├── experts/ ← 9 expert panel definitions
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│ ├── scoring-rubrics/ ← 5 scoring rubric templates
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│ └── ...
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├── outbound-engine/ ← Cold outbound automation
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│ ├── SKILL.md
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│ ├── scripts/
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│ ├── references/ ← ICP template, copy rules
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│ └── ...
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├── seo-ops/ ← SEO intelligence
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│ ├── SKILL.md
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│ ├── content_attack_brief.py
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│ ├── gsc_client.py
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│ ├── trend_scout.py
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│ └── ...
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└── finance-ops/ ← Financial analysis
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├── SKILL.md
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├── scripts/
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├── references/ ← Metrics, rates, ROI models
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└── ...
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```
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---
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## 🤝 Contributing
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Found a bug? Have an improvement? PRs welcome.
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1. Fork the repo
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2. Create your feature branch (`git checkout -b feature/better-scoring`)
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3. Commit your changes
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4. Push to the branch
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5. Open a Pull Request
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---
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## 📄 License
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MIT License. Use these however you want.
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---
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## 🏢 About
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Built by the marketing engineering team at [Single Grain](https://www.singlegrain.com). We help B2B companies grow with AI-powered marketing and sales operations.
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**Want these skills managed for you?** [Talk to us](https://www.singlegrain.com/contact/) — we run these systems for companies doing $10M-$500M in revenue.
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---
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*Star this repo if you find it useful. It helps others discover these tools.*
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