vibetrading

What This Skill Does

The vibetrading skill provides an agent-first framework designed to streamline the lifecycle of cryptocurrency algorithmic trading. At its core, it allows developers and power users to write trading strategies as Python functions using the @vibe decorator. The primary benefit of this framework is its seamless environment parity: the exact same code used to define your strategy can be executed in a high-fidelity historical backtest or deployed directly to live exchanges like Hyperliquid, Paradex, Lighter, or Aster. The framework handles the complexities of fetching real-time market data, managing orders, and tracking account margins, allowing the agent to focus purely on the logic of the trade.

Installation

To integrate vibetrading into your environment, use the OpenClaw management CLI: clawhub install openclaw/skills/skills/crabbytt/vibetrading

For local development and execution, ensure you have the required Python dependencies installed: pip install vibetrading (Core) pip install "vibetrading[hyperliquid]" (Live trading capabilities) pip install "vibetrading[dev]" (Tooling for testing and linting)

Use Cases

• Strategy Prototyping: Rapidly convert natural language ideas into executable Python code for crypto asset classes.
• Backtesting: Evaluate historical performance using specific intervals (e.g., 1h, 5m) and slippage parameters to ensure strategies hold up before committing capital.
• Live Deployment: Connect your agent to decentralized exchanges (DEXs) to execute trades automatically based on your defined logic.
• Portfolio Risk Management: Build sophisticated logic for position sizing, leverage control, and stop-loss/take-profit automation.

Example Prompts

1. "Create a trading strategy for BTC that uses the RSI indicator to enter long positions when the asset is oversold and sets a stop-loss at 2%."
2. "Run a backtest on my current ETH strategy over the last 30 days of 1-hour data and report the Sharpe ratio and max drawdown."
3. "Deploy my moving average crossover strategy to Hyperliquid with 3x leverage, ensuring it checks that available margin is over $100 before every trade."

Tips & Limitations

Always ensure your strategy includes a check for math.isnan(price) to prevent runtime errors during the initial data loading phase. When developing, remember that this framework is strictly for crypto assets; it does not support traditional stocks or forex markets. Always prioritize safety by incorporating set_leverage limits and strictly adhering to the margin > 50 validation rules provided by the SDK to avoid liquidation risks. When backtesting, adjust your slippage_bps to match the expected liquidity of the target asset for more realistic results.