vibetrader

What This Skill Does

VibeTrader is a powerful OpenClaw agent skill designed to bridge the gap between complex financial markets and natural language control. It empowers users to build, monitor, and execute sophisticated trading strategies for stocks, ETFs, crypto, and options without needing to write complex code. By leveraging an AI-driven backend, VibeTrader allows you to describe your trading logic in plain English—such as setting thresholds for technical indicators—and have the agent execute trades or manage your portfolio accordingly. It provides a comprehensive interface for viewing real-time quotes, tracking positions, and performing backtests, making it an essential tool for both novice traders looking for automated assistance and experienced traders needing to streamline their manual operations.

Installation

To integrate VibeTrader into your OpenClaw environment, you first need to generate an API key from the official VibeTrader dashboard at vibetrader.markets/settings. Once you have your key, you have two primary methods for configuration. You can add the key directly to your ~/.openclaw/openclaw.json configuration file under the 'skills' object using the 'VIBETRADER_API_KEY' environment variable. Alternatively, you can set the environment variable within your shell session by running export VIBETRADER_API_KEY="your_key_here". For users utilizing the MCP protocol, you can initialize the skill by running the command clawhub install openclaw/skills/skills/etbars/vibetrader. Once installed, verify the connection by checking the health status endpoint or listing your existing bots.

Use Cases

VibeTrader is ideal for automated technical analysis, portfolio rebalancing, and risk management. You can use it to set up 'set-and-forget' bots that monitor RSI or moving averages, allowing the agent to enter or exit positions based on your predefined criteria. It is also excellent for gathering real-time market intelligence, such as pulling complex options chains to evaluate volatility or checking current market status before executing a manual trade. Because it supports both paper and live trading, it is a perfect sandbox for testing new market theories without risking capital before graduating to a live production environment.

Example Prompts

1. "Create a paper trading bot that buys 10 shares of NVDA every time the 14-day RSI drops below 35."
2. "What are my current open positions in my live account and what is my total account balance?"
3. "Show me the current options chain for TSLA with a strike price near 250 and include the Greeks."

Tips & Limitations

Always start by testing your strategies in the paper trading mode to ensure the logic behaves as expected. While the AI is adept at interpreting trading intent, it is still a tool; double-check the 'limit' or 'stop-loss' parameters when creating bots to protect your capital. Note that market data latency can occur depending on your connection to the base API, and always ensure your API key has the necessary permissions. Avoid relying on the agent for high-frequency trading, as latency in the LLM processing loop may impact execution speed compared to direct algorithmic trading platforms.