vibetrading-code-gen

What This Skill Does

The vibetrading-code-gen skill is an advanced automation tool designed to bridge the gap between abstract trading concepts and functional Python code for the Hyperliquid exchange. By acting as a specialized development assistant, it translates natural language requirements into complete, production-ready trading strategies. The skill handles complex boilerplate tasks, including API authentication, WebSocket connection management, order execution logic, and rigorous error handling. Beyond simple generation, it integrates an automated validation engine that ensures every line of code meets syntax standards and maintains compatibility with required system environments. This allows traders to focus on strategy logic while the tool manages technical debt and code quality.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/liuhaonan00/vibetrading-code-gen Ensure you have your environment configured with the necessary Python dependencies as outlined in the generated requirements.txt file once the skill is active.

Use Cases

This skill is ideal for:

1. Rapid prototyping of technical analysis strategies (e.g., RSI, MACD, or Bollinger Bands).
2. Constructing institutional-grade grid trading bots with customized price ranges and stake sizes.
3. Integrating external VibeTrading signals directly into automated order management systems.
4. Developing custom market-making logic where precision in order placement and cancelation is critical.

Example Prompts

• "Generate a Mean Reversion strategy for BTC using Bollinger Bands with a 20-period lookback, entering long when the price touches the lower band and exiting at the mean."
• "Create a Hyperliquid grid bot for ETH/USDC. Use 20 grids ranging from 2500 to 3000, with an order size of 0.05 ETH per grid."
• "Build a strategy that listens to VibeTrading signals. On a 'Bullish' signal, place a market buy for 0.1 SOL, and on 'Bearish', perform a market sell to close the position."

Tips & Limitations

To get the best results, provide specific parameter values for indicators and risk management thresholds. Always review the generated code before deploying to a live account. While the validator handles syntax and imports, it cannot verify the underlying profitability of a strategy. Always run the generated code in a paper-trading environment or using the Hyperliquid testnet first. The validator is designed to enforce Python 3.5+ safety, so avoid using cutting-edge library features that might conflict with the compatibility settings.