What problem does it solve? Offline insight engines can overwhelm users with too many banners, notifications, and reminders. This Skill defines frequency caps, quiet hours, and per-type cooldowns so an Android app respects user attention instead of saturating it. ## Core Features & Use Cases - Temporal debouncing: Kotlin decision functions that enforce minimum intervals (e.g., 72h between automatic insights, 24h when the user opts into more) backed by DataStore timestamps. - Quiet hours and user preferences: Preference models for enabling/disabling insights, requesting more or fewer, and blocking delivery during configurable nighttime windows. - Notification throttling and prioritization: A daily notification counter with priority rules (Bitácora > Rutina > Insight), plus per-insight-type 7-day cooldowns and feedback-driven rule disabling. - Use Case: When building a journaling or wellness app that surfaces offline-generated insights, apply these policies so the user sees at most a few well-timed insights per week instead of one after every log entry. ## Quick Start Apply the debouncing strategies skill to configure how often insights, banners, and local notifications are shown to the user.