A powerful backtesting engine to simulate and optimize cryptocurrency trading strategies using historical market data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install crypto-simulator
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 crypto-simulator 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 Crypto Simulator?
The Crypto Simulator is a comprehensive technical tool designed for developers and traders to evaluate the performance of various trading algorithms against historical market data. By leveraging real-time and historical data from CoinGecko, this Openclaw Skills entry allows users to simulate popular strategies like RSI Swing, Moving Average Crossovers, and Grid trading without any financial risk.
This skill bridges the gap between theoretical strategy design and market reality. It provides a robust framework for validating entry and exit signals, ensuring that your automated trading logic is grounded in historical evidence. Whether you are building a custom bot or researching market trends, this addition to the Openclaw Skills library provides the necessary analytical depth to make informed decisions.
Crypto Simulator Use Cases
- Backtesting technical indicators like RSI, MACD, and Bollinger Bands against historical price action.
- Comparing the performance of different investment approaches, such as DCA versus HODL, over specific timeframes.
- Optimizing strategy parameters to find the most profitable settings for specific assets like Bitcoin or Ethereum.
- Serving strategy data via a REST API to power external dashboards or trading bots.
How Crypto Simulator Works
- The skill fetches historical price data for the specified cryptocurrency from the CoinGecko API.
- It applies the selected trading strategy logic (e.g., buying when RSI is below 30) to the historical dataset.
- The simulation engine calculates trade execution, accounting for price movements and generating performance metrics.
- Results are output via the CLI or made available through the integrated REST API for further analysis.
- Frequent data requests are cached locally in a SQLite database to maintain efficiency and stay within API rate limits.
Crypto Simulator Setup
To get started with this skill, navigate to the directory and install dependencies:
cd {skill_dir}
npm install && npm run build
You can then run a backtest immediately using the CLI:
node dist/cli.js backtest --coin bitcoin --strategy rsi_swing --days 90
Crypto Simulator Data Schema & Taxonomy
The skill organizes data using a structured SQLite cache and provides output through a consistent API schema.
| Component | Type | Description |
|---|---|---|
| SQLite DB | Persistent | Caches historical price data in the ./data directory |
| REST API | JSON | Provides endpoints for prices, backtest results, and optimization logs |
| CLI Output | Terminal | Detailed tables showing profit/loss, trade count, and strategy success rates |
Crypto Simulator Advanced Features
- Multi-strategy comparison to benchmark different approaches side-by-side using Openclaw Skills.
- Automated parameter optimization to discover the ideal settings for indicators like moving average periods.
- Built-in REST API server for seamless integration with web applications and remote monitoring tools.
- Robust local caching mechanism to minimize external API dependency and handle rate-limiting gracefully.
SKILL.md
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