How to Contribute to an Open-Source AI Trading Bot
If you want to contribute to an open-source AI trading bot — and build on a real, running system instead of a toy — this guide shows you exactly how. The Claude-powered crypto bot from Part 1 is MIT-licensed on GitHub, and the most interesting problems in it are wide open. You don’t need to be a quant or an ML expert; there’s meaningful work here for developers, traders, writers, and testers alike.
👋 New to open source? That’s fine — this is a friendly, low-pressure project. A thoughtful question or a docs fix is a real contribution.
Why Contribute to This Project?
Most “AI trading bot” repos are either abandoned demos or paywalled black boxes. This one is different: it’s a complete, documented, honestly-evaluated system where the central question — does it actually have a tradeable edge? — is genuinely unsolved. Contributing here means working on real LLM-agent orchestration, machine-learning signal modelling, exchange execution, and a production dashboard, with a maintainer who’ll actually review your PR. It’s a great portfolio piece and a great way to learn.
Where Help Is Most Needed
Pick whatever matches your skills:
Area Example contributions 🧠 Strategy & research New signals, better entry/exit logic, ideas to capture trend (the current strategy is defensive and lags in bull markets) 📈 ML modelling Feature engineering, calibration, honest walk-forward evaluation, reducing overfitting 🛡️ Risk & execution Smarter sizing, OCO/bracket orders, slippage modelling, live-trading safety 💻 Dashboard (Next.js) New visualizations, UX, mobile polish, accessibility 🔧 DevOps A one-commanddocker compose setup — the single highest-impact task right now
📖 Docs & testing
Setup guides, tutorials, backtest rigor, unit tests, translations
Setting Up the Project Locally
You don’t need a VPS to contribute — run it locally on testnet:
git clone https://github.com/dineshstack/crypto_bot.git
cd crypto_bot
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt
cp .env.example .env # add your own keys; keep TESTNET=true
For the dashboard:
cd dashboard
npm install
cp .env.local.example .env.local
npm run dev
How to Submit Your First Pull Request
The flow is standard GitHub — small, focused changes are the easiest to merge:
git checkout -b feature/your-improvementmake your change
python3 -m py_compile changed_file.py # sanity-check Python
git commit -m "Clear description of what changed and why"
git push origin feature/your-improvement
then open a Pull Request against main
In your PR, describe what you changed, why, and how you tested it. Anything touching order execution, sizing, or the circuit breakers gets extra review — describe your testing in detail, and never weaken a safety check without explaining why. The full checklist is in the repo’s CONTRIBUTING.md.
Not a Coder? You Can Still Help
Some of the most valuable contributions aren’t code:
- 🐛 Report bugs or unexpected behaviour with clear steps to reproduce.
- 💡 Suggest strategy ideas or share how it behaved in a market regime you tested.
- 📝 Improve the docs — even a typo fix or a clearer sentence helps the next person.
- ⭐ Star and share the repo — reach is what brings in more contributors.
Look for issues labelled good first issue to get started.
Let’s Build Something Honest Together
This project is deliberately transparent about what it can and can’t do, which makes it a rare thing in the “AI trading” space: a place to genuinely learn and experiment without hype. If that appeals to you, jump in.
🚀 Ready to contribute?
⭐ Star & fork the repo
💬 Open an issue describing what you’d like to work on
☕ Not contributing code but want to support the work? Buy me a coffee on Ko-fi — it keeps the demo and API running.


Related posts
- Part 1 — How I Built an AI Crypto Trading Bot with Claude AI
- Part 2 — Deploy an AI Crypto Trading Bot to Your VPS
Tags: Open Source, AI Trading Bot, Contributing, GitHub, Developer Community
Disclaimer: For educational and research purposes only. Not financial advice. Cryptocurrency trading carries substantial risk of loss.
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