name: TauricResearch-Skill description: "This skill should be used when the user asks to analyze a stock, perform fundamental or technical trading analysis, run the Tauric framework, debate a stock's potential, or generate a trading decision. It executes the TauricResearch LangGraph trading pipeline." metadata: { "openclaw": { "emoji": "📈" } }
TauricResearch-Skill
This skill provides access to the TauricResearch TradingAgents framework, a multi-agent system that simulates a real-world trading firm. It employs a team of LLM analysts (Fundamentals, News, Sentiment, Technical) and a debate engine (Bull vs. Bear) to arrive at high-conviction trading decisions.
When to use this skill
Activate this skill when the user requests:
- "Analyze [TICKER] using Tauric"
- "Run a fundamental analysis on AAPL"
- "Should I buy or sell NVDA?"
- "Start a trading debate on MSFT"
- "What is the market sentiment for TSLA?"
How to execute
This skill relies on a Python pipeline located in this directory.
To run an analysis for a specific ticker (e.g., AAPL), execute the following command:
cd ~/.openclaw/skills/TauricResearch-Skill && python cli/main.py --ticker AAPL
Supported Arguments
--ticker: The stock symbol to analyze (e.g., NVDA, MSFT).--rounds: (Optional) The number of debate rounds between the Bull and Bear agents (default: 2).
Pipeline Execution Details
When executed, the system will output logs to the console as it performs the following steps:
- Data Collection: Gathers stock data, fundamentals, technical indicators, and breaking news using LangGraph Tools.
- Analysis: Specialized agents (Flash, Macro, Pulse) generate individual reports.
- Debate: The Bull and Bear agents debate the merits and risks of the trade based on the reports.
- Decision: A final Trader/Risk node evaluates the debate and determines the optimal action (BUY/SELL/HOLD).
You should present the final output and decision summary to the user in a clear, formatted message.