oh-my-growth — Open-Source Growth Decision Engine

An open-source AI growth strategy tool for SEO, AEO, GEO, product growth, and AI-agent teams.

Turn a growth question into a ranked, evidence-linked 2-week experiment with a success signal and a stop condition—not a generic list of tactics.

For: growth leads, founders, product teams, and AI agents using Claude Code, OpenClaw, Hermes, or the local growth CLI.

Install from PyPI · See a real command · Star or fork on GitHub · 中文文档

---

What is oh-my-growth?

oh-my-growth is a growth decision-support system, not an analytics dashboard or an autonomous ad-buying tool. It combines a versioned growth knowledge base with decision logic to help a team choose a small, testable next move.

If you need to…	oh-my-growth returns…
Decide what to test first	A ranked set of actions with rationale and risks
Diagnose acquisition, retention, monetization, or referral	The stage, core tension, metric, and missing context
Improve SEO, AEO, or GEO / LLM discovery	A search-visibility experiment tied to a conversion goal
Reuse a decision in a team or agent workflow	Operator, executive, JSON, decision-memo, or public-safe share views

Use it when the question is “what should we validate next?”—not when you only need a dashboard of existing metrics.

When to use it

When your DAU drops 20%, oh-my-growth helps you:

1. Identify the core tension in 3 minutes
2. Get priority ranking of what to do first
3. Match 3 similar success cases
4. Generate a 2-week experiment plan

Use it inside Claude Code, OpenClaw, or Hermes Agent, or from any terminal with the standalone CLI.

Core User Personas

Persona	Common Problem	Key Command	Value
🎯 Growth Hacker	"Need reference cases for experiment design"	/omg-match	Find similar cases in seconds
📊 Product Manager	"Growth strategy priority is unclear"	/omg-diagnose	Get priority ranking instantly
🚀 Startup Founder	"Limited resources, don't know where to start"	/omg-cold-start	Focus on highest-impact actions

---

✨ Example: 5-Minute Diagnosis

User Input:

/omg-diagnose My DAU dropped 20%, what should I do?

oh-my-growth Output:

┌─────────────────────────────────────────────────────────┐
│  📌 Stage Diagnosis                                     │
├─────────────────────────────────────────────────────────┤
│  Scaling Stage · User Retention Problem                 │
│  North Star: Weekly Active Users                        │
│                                                         │
│  📌 Core Tension                                        │
│  Not product quality, but engagement loop is broken     │
│                                                         │
│  📌 Priority Ranking                                    │
│  Re-engage power users > Fix onboarding > New features  │
│                                                         │
│  📌 Matched Cases (Top 3)                               │
│  1. Slack's re-engagement strategy (92% match)          │
│  2. Notion's power user program (87% match)             │
│  3. Duolingo's streak feature (82% match)               │
│                                                         │
│  📌 2-Week Experiment                                   │
│  1. Email inactive users with personalized value        │
│  2. Track weekly active users, not DAU                  │
│  3. Stop if no improvement in 2 weeks                   │
└─────────────────────────────────────────────────────────┘

---

📦 Install

Choose the host you already use. Each command installs the same knowledge base and decision engine.

Fastest standalone install from PyPI:

uv tool install oh-my-growth
growth --help

Claude Code

git clone https://github.com/tinylion1024/oh-my-growth.git && cd oh-my-growth && ./scripts/install.sh --platform claude

OpenClaw

git clone https://github.com/tinylion1024/oh-my-growth.git && cd oh-my-growth && ./scripts/install.sh --platform openclaw

Hermes Agent

git clone https://github.com/tinylion1024/oh-my-growth.git && cd oh-my-growth && ./scripts/install.sh --platform hermes

Standalone CLI

Recommended for macOS and other developer machines — isolated install with uv:

brew install uv
uv tool install oh-my-growth
growth --help

Install with pip in a virtual environment:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install oh-my-growth
growth --help

Homebrew Python intentionally blocks global pip install commands (PEP 668). Use uv above, pipx install oh-my-growth, or a virtual environment instead of --break-system-packages.

Get your first recommendation:

growth diagnose "How can my SaaS get its first 1,000 users?" \
  --industry saas \
  --stage 0-1 \
  --problem acquisition

Verify Installation

In Claude Code:

/omg-diagnose test installation

Supported Platforms:

• ✅ Claude Code
• ✅ OpenClaw
• ✅ Hermes Agent
• ✅ Standalone CLI

---

✨ Quick Start

Standalone CLI

Use growth from any terminal after installation. Add only the context you know; the tool will identify missing inputs and suggest the next experiment.

growth fast-scan "Should we test a referral loop?" \
  --industry saas \
  --stage 1-10 \
  --problem referral

For a complete decision report, use growth diagnose ...; run growth --help to see all commands.

Most Used Commands

Strategy Diagnosis (Use when: problem is unclear)

/omg-diagnose How to get first 1000 users for SaaS

Case Matching (Use when: need reference cases)

/omg-match Referral growth cases in education industry

Opportunity Assessment (Use when: evaluate feasibility)

/omg-assess Should we do referral program?

Strategy Design (Use when: need execution plan)

/omg-design How to improve monthly active user retention

Scenario Shortcuts

/omg-cold-start      # First 1000 users
/omg-retention       # Improve retention
/omg-monetization    # Design pricing
/omg-referral        # Plan referral program

Command Reference

Core commands:

• /omg-assess - opportunity assessment
• /omg-diagnose - full growth diagnosis
• /omg-design - strategy design
• /omg-fast-scan - fast feasibility check
• /omg-brd - decision BRD draft
• /omg-match - similar case matching
• /omg-learn - learning path generation

Utility commands:

• /omg-search - search cases, plays, and theories
• /omg-validate - validate report quality

Scenario commands:

• /omg-cold-start - early acquisition
• /omg-retention - retention diagnosis
• /omg-monetization - monetization design
• /omg-referral - referral planning

View references:

• weekly
• experiment-card
• share
• decision-memo
• qbr

---

🎯 Why oh-my-growth?

Core Differentiators

Feature	oh-my-growth	ChatGPT/Claude Native	GrowthHackers
Structured Knowledge	✅ 81 cases, 111 plays, 7 method packs	❌ No structured knowledge	✅ Community cases
Decision Engine	✅ Bayesian + Kelly + Game Theory	❌ No decision framework	❌ No decision framework
Instant Diagnosis	✅ 5-minute output	⚠️ Requires iteration	❌ Manual research
Executable Output	✅ 2-week experiment plan	⚠️ Generic advice	❌ Case aggregation only
AI-Powered	✅ RAG-enhanced	✅ Native AI	❌ Not AI-powered

Knowledge Base Scale

• 81 Cases — Notion, Airbnb, TikTok, GPT-4o, Claude 3.5, Pinduoduo...
• 111 Growth Plays — Referral, PLG, Content Growth, Retention...
• 12 Theory Schools — Growth Hacking, Network Effects, PLG...
• 7 Growth Method Packs — SEO/AEO, GEO/LLM, CRO, paid acquisition, GTM, lifecycle, referral...
• 7 Learning Modules — Cold start, Retention, Monetization...

→ Browse Full Case Index · → Browse Full Play Index

---

📊 Representative Outputs

The following are illustrative scenarios that show the expected output shape. They are not customer outcome claims. We are collecting anonymized, reproducible user case studies; see how to contribute a case.

Case 1: SaaS Cold Start

Problem: "How to get first 1000 users for my AI writing SaaS?"

oh-my-growth recommended:

1. Focus on "Beta Invite" (not ads or viral growth)
2. Matched 3 cases: Notion, Calendly, Dropbox
3. 2-week experiment: Manual outreach to 50 target users

Success signal: acquire 3 paid customers from 50 founder-led outreach attempts

Case 2: Retention Drop

Problem: "My DAU dropped 20% after product update"

oh-my-growth diagnosed:

1. Core tension: Feature confusion, not product quality
2. Priority: Re-engage power users > Rollback features
3. Matched case: Slack's onboarding improvement

Success signal: improve D7 retention before scaling acquisition

Case 3: Monetization Strategy

Problem: "How to design pricing for my B2B SaaS?"

oh-my-growth designed:

1. Three-tier pricing: Free → Pro ($29) → Enterprise ($299)
2. Matched cases: Notion, Linear, Slack
3. Key principle: Free tier for PLG, Pro tier for revenue

Success signal: validate willingness to pay and retention guardrails before rollout

---

🛠️ Advanced Features

Decision Engine

Bayesian Decision Framework:

/omg-assess Should we invest $50K in referral program?

• Evaluates evidence strength (A/B/C/D tier)
• Calculates probability of success
• Recommends: RUN_EXPERIMENT / NEED_MORE_DATA / DO_NOT_INVEST

Kelly Allocation:

/omg-design How to allocate growth budget?

• Optimal resource allocation across channels
• Risk-adjusted experiment sizing

Knowledge Router

Automatically routes your question to the right knowledge base:

• Case database (81 cases)
• Play database (111 plays)
• Theory database (12 schools)
• Method pack database (7 operating systems)

Output Validation

/omg-validate my-strategy-report.md

Checks if your report covers:

• ✅ Core tension identified
• ✅ Priority ranking provided
• ✅ 2-week experiment defined
• ✅ Success metrics specified

---

📚 Documentation

• Full Command Reference — all CLI commands, views, and output modes
• GEO / LLM Discovery Use Case — AI-search visibility workflow
• SEO / AEO Growth Diagnosis — organic acquisition workflow
• Case Study Library — growth cases and indexed examples
• Growth Playbook — proven plays and tactics
• Theory Frameworks — growth theories and schools
• API Documentation — CLI contract, retrieval surfaces, and output views

❓ FAQ

What is oh-my-growth?

oh-my-growth is a growth strategy external brain. It combines a structured knowledge base, multi-agent decision logic, and reusable experiment planning for acquisition, retention, monetization, and referral work.

Who is it for?

It is designed for growth operators, founders, PMs, and AI assistants that need grounded growth answers, not generic advice.

Does it replace product analytics, a BI tool, or a growth team?

No. Bring the metrics, constraints, and prior experiment history you already have. oh-my-growth helps turn that context into a decision, an experiment design, and explicit success and stop signals.

Can I use it without an AI-agent host?

Yes. Install the PyPI package and use growth diagnose, growth design, growth fast-scan, or growth search from a terminal. Claude Code, OpenClaw, and Hermes are additional integration surfaces, not prerequisites.

Why does this help SEO and GEO?

The repository exposes searchable keywords, explicit command references, canonical docs, and an AI-readable llms.txt entry point so agents and LLMs can understand what the project does. For Google-style search, GEO/AEO work still depends on crawlable, useful, well-structured SEO content.

---

🌟 Community

• Star the repository if evidence-backed growth decisions are useful to your team; it makes the project easier for other builders to discover.
• Fork it if you want to add a vertical knowledge base, adapt the decision logic, or integrate a new agent host; the project is MIT-licensed.
• GitHub Issues: report a bug, request a case, or propose an improvement.
• GitHub Discussions: share a use case or compare implementation notes.
• Case contributions: add an anonymized, evidence-backed case via the contribution guide.
• Twitter/X: @ohmygrowth.

---

📈 Roadmap

For current priorities and how to influence them, see the public roadmap.

Q3 2026

• Web UI for non-technical users
• Vectorized case search (semantic matching)
• Team collaboration features

Q4 2026

• Pro version ($29/month)
• Custom case library
• API access

2027

• Enterprise version ($299/month)
• Private deployment
• Advanced analytics dashboard

---

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Ways to contribute:

• 📝 Add new growth cases
• 🛠️ Improve decision engine
• 📖 Translate documentation
• 🐛 Report bugs

---

📄 License

MIT License — see LICENSE for details.

---

🙏 Acknowledgments

Built with inspiration from:

• GrowthHackers — Community-driven growth knowledge
• Reforge — Growth strategy frameworks
• OpenAI ChatGPT — AI-powered reasoning

Special thanks to all contributors and case study authors.

---

Install from PyPI · Read Full Docs · Contribute a case · Star or fork on GitHub

Made with ❤️ by Growth Master Team