What problem does it solve? Android exposes dozens of hardware sensors, but raw dumpsys output is hard to interpret and sensor names vary by manufacturer. This Skill provides a structured reference of 26 commonly useful sensors with their raw data formats, use cases, and composite inference patterns so you can infer device state, user activity, and environment without app-level APIs. ## Core Features & Use Cases - Sensor Catalog: Covers motion, orientation, environmental, activity recognition, event detection, and specialty sensors with raw data formats and interpretation guidance. - Composite Inference Patterns: Pre-built multi-sensor logic for detecting late-night screen use, phone calls, gaming sessions, and abandoned devices. - Quick ADB Commands: Ready-to-run dumpsys sensorservice commands for listing, filtering, and inspecting sensors on any Android device. - Use Case: You want to detect whether a user is using their phone late at night in a dark room. Combine ambient light (< 5 lux), screen state (Awake), and time of day following the documented inference pattern. ## Quick Start Ask the AI to list all sensors on the connected Android device and explain which ones can detect late-night phone usage.
