Clarity-Digital-Twin/big-mood-detector

AI Summary: Implement two new command-line flags for the Big Mood Detector: `--auto-find-window` to automatically select the best prediction window from available Apple Health data, and `--show-windows` to display all available windows before processing. This involves creating a `WindowFinder` service to identify and rank suitable data windows based on criteria like recency, length, and data quality, and integrating these flags into the existing CLI.

AI Summary: Implement a two-phase XML processing system for the Big Mood Detector application. Phase 1 involves a fast scan to identify available data types in large Apple Health XML export files. Phase 2 uses this information to create a processing plan, allowing users to selectively process only the necessary data and improving performance and user experience. This requires creating an XML probe, a plan builder, and integrating them with the existing parser.