A 1-minute crypto guard agent uses LLMs as builders, not predictors

The system watches high-volatility crypto assets, specifically BTC and ZEC, in a 60-second loop. It does not use an LLM as a price-prediction oracle. Instead, it runs a local RandomForestClassifier with strict human-designed guardrails to enforce risk rules and reduce emotion-driven trading mistakes.

The setup runs locally on Windows with WSL Ubuntu, using plain scripts instead of wrapper packages, and is designed to run around the clock. Tree-based machine learning can react too slowly during sudden short squeezes or liquidation cascades because it judges new moves against past patterns and may output overly cautious probabilities. The design treats this as right-side lag and uses one-minute scanning to reduce delayed action.

Claude is used as an execution co-pilot for engineering problems such as feature drift, right-side lag, and network instability, rather than as the live decision maker.