Dockkit

This is for apps that need to work with motorized iPhone stands like Belkin's MagSafe tracking mount. The framework handles the motor control and subject detection automatically through built-in ML, so you get pan and tilt tracking without writing computer vision code. System tracking runs out of the box with AVFoundation cameras, or you can disable it and feed your own Vision observations for custom behavior. The framing modes are nice if you need subjects positioned left or right instead of centered, which matters when you have UI overlays eating screen real estate. Requires iOS 17 and real hardware since the Simulator obviously can't talk to motors. Good for video calling apps, content recording tools, or anything where keeping a person in frame matters more than the camera operator.

skills.sh installs: 3.2K
GitHub stars: 1.3K
last updated: Aug 21, 2026

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Install

$ npx -y skills add dpearson2699/swift-ios-skills --skill dockkit --agent claude-code

Installs into .claude/skills of the current project.

Files

DockKit

Framework for integrating with motorized camera stands and gimbals that physically track subjects by rotating the iPhone. DockKit handles motor control, subject detection, and framing so camera apps get 360-degree pan and 90-degree tilt tracking with no additional code. Apps can override system tracking to supply custom observations, control motors directly, or adjust framing. iOS 17+, Swift 6.3.