What problem does it solve? Manually logging goal progress (study notes, workouts, work tasks, habits) is tedious and easy to forget. This Skill automatically detects goal-related images in conversation, uses a VLM to extract key information, and records structured check-in entries into your daily notes. ## Core Features & Use Cases - Automatic Image Detection: Triggers when users send goal-related images such as study notes, fitness records, progress screenshots, or habit check-in calendars. - VLM-Based Recognition: Uses goal-type-specific prompts (study, fitness, work, creation, habit) to extract tasks, completion rates, and quantitative metrics like time, weight, or word count. - Structured Diary Logging: Writes formatted check-in entries with tables, key data, and remarks into the daily note via the edit_daily tool, then asks the user to confirm accuracy. - Use Case: A user sends a photo of their handwritten English vocabulary list at 20:00. The Skill recognizes 15 new words completed, estimates progress, and logs a timestamped study check-in entry to the day's notes. ## Quick Start Send a photo of your study notes or workout record and ask the assistant to recognize it and log today's goal check-in to your daily notes.
