mmr-loop-skill

AI-driven portfolio monitoring automates the continuous scanning of your trading portfolio for changes and potential opportunities. This Skill uses LLM-driven logic to generate trade proposals with confidence scores and reasoning, requiring user approval before execution.

You need to load the 'mmr' skill first and ensure Python with associated libraries is installed for real-time data processing. These prerequisites provide the environment required to run the trading loop and generate proposals with confidence scores.

No, the LLM-driven trading loop generates trade proposals complete with confidence scores and reasoning, which explicitly require your manual review and approval before any execution occurs. It manages risk and monitors opportunities without auto-executing trades.

Automated trading handles risk management by continuously scanning a diversified portfolio for changes and managing exposure through AI-driven proposal generation. It identifies opportunities and manages administrative workflows to reduce manual oversight while maintaining risk controls.

A key limitation of this automated portfolio management loop is its strict dependency on the 'mmr' skill and Python libraries for real-time data processing. Additionally, it cannot act autonomously, as every generated trade proposal requires manual user approval before execution.