An automated sandbox that transforms natural language trading intents into executable Python backtesting strategies.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install trading-devbox
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install trading-devbox using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Trading DevBox?
Trading DevBox is a powerful development sandbox designed for traders and developers who want to validate their ideas without manual coding overhead. By utilizing Openclaw Skills, this tool interprets human language descriptions of trading strategies—such as specific entry drops or profit targets—and generates structured, executable Python code. This allows for a seamless transition from a conceptual trading plan to a technical backtest, significantly reducing the time required for quantitative research and strategy refinement.
The skill provides a standardized environment for testing hypotheses across various crypto assets like BTC, ETH, and SOL. Through the integration of Openclaw Skills, users can iterate on their parameters in real-time, ensuring that every strategy is mathematically sound before moving to live environments.
Trading DevBox Use Cases
- Rapidly converting a verbal trading idea into a functional backtest script.
- Testing specific market scenarios like buying a 10% dip and selling at a 30% gain.
- Validating exit strategies including take-profit and stop-loss levels across different timeframes.
- Generating boilerplate Python code for the backtrader framework to jumpstart custom development.
How Trading DevBox Works
- The agent analyzes the user's natural language input to extract key parameters like asset type, entry conditions, and exit thresholds.
- Extracted parameters are presented to the user for confirmation to ensure the logic matches the intent.
- A dedicated directory is created and a Python script is dynamically generated using the backtrader library.
- The script is executed within the sandbox environment to simulate the strategy performance.
- The results and execution status are reported back to the user in their preferred language.
Trading DevBox Setup
To use this skill effectively, ensure your environment has Python 3 installed along with the necessary backtesting libraries. You can prepare your local environment by running:
mkdir -p /tmp/trading-devbox
pip install backtrader
Once the environment is ready, the Openclaw Skills framework will handle the creation and execution of strategy files automatically.
Trading DevBox Data Schema & Taxonomy
The skill organizes its operations through a temporary file system and structured parameters:
| Data Point | Details |
|---|---|
| Strategy File | Located at /tmp/trading-devbox/strategy.py |
| Logic Framework | Uses the backtrader Python library for strategy simulation |
| Parameters | Structured as a JSON object including entry_drop_pct, take_profit_pct, and stop_loss_pct |
| Output | JSON-formatted status messages and performance summaries |
Trading DevBox Advanced Features
- Support for multi-lingual natural language processing to define strategies.
- Automated directory management for clean strategy execution and isolation.
- Integration with the industry-standard backtrader framework for extensible analysis.
- Dynamic parameter adjustment based on real-time user feedback within the Openclaw Skills workflow.
SKILL.md
Loading
Related Openclaw Skills
clawned
A security-focused agent that inventories installed skills and performs threat analysis to ensure your AI ecosystem remains secure.
WhatsApp Business Responder
An intelligent customer support agent that automates responses and escalates complex queries for small businesses using the WhatsApp Business API.
Razorpay Monitor
An autonomous monitoring assistant that tracks Razorpay payment flows, alerts you of failures, and delivers revenue summaries via WhatsApp or Telegram.
India Market Pulse
An AI-powered financial assistant providing real-time Indian stock market updates and automated price alerts through Openclaw Skills.
ai-app-lab
A comprehensive repository of 27 AI application templates and reference architectures built on Volcengine infrastructure.
Creator Intel V5
A hard-tech intelligence aggregator that filters out marketing hype to deliver pure engineering specifications and architectural insights.
Featured*
