MCPInstall

dockkit

Control motorized camera docks and enable intelligent subject tracking using DockKit. Use when discovering DockKit-compatible accessories, implementing camera subject tracking for faces or bodies, controlling dock motors for pan and tilt, configuring framing behavior, setting regions of interest, or building video apps with automatic camera tracking.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/dpearson2699/swift-ios-skills --skill dockkit
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads dockkit automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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.

Contents

Setup

Import DockKit:

import DockKit

DockKit requires a physical DockKit-compatible accessory and a real device. The Simulator cannot connect to dock hardware.

DockKit itself requires no special entitlements or DockKit-specific Info.plist keys. Camera apps that use device cameras still need normal camera privacy handling, including NSCameraUsageDescription. The framework communicates with paired accessories automatically through the DockKit system daemon.

The app must use AVFoundation camera APIs. DockKit hooks into the camera pipeline to analyze frames for system tracking.

Discovering Accessories

Use DockAccessoryManager.shared to observe dock connections:

import DockKit

func observeAccessories() async throws {
    for await stateChange in try DockAccessoryManager.shared.accessoryStateChanges {
        switch stateChange.state {
        case .docked:
            guard let accessory = stateChange.accessory else { continue }
            // Accessory is connected and ready
            configureAccessory(accessory)
        case .undocked:
            // iPhone removed from dock
            handleUndocked()
        @unknown default:
            break
        }
    }
}

accessoryStateChanges emits DockAccessory.StateChange values with state, accessory, and trackingButtonEnabled. Use accessory.identifier for the name, category, and UUID; hardware details are available via firmwareVersion and hardwareModel.

System Tracking

System tracking is DockKit's default mode. When enabled, the system analyzes camera frames through built-in ML inference, detects faces and bodies, and drives the motors to keep subjects in frame. Any app using AVFoundation camera APIs benefits automatically.

Enable or Disable

// Enable system tracking (default)
try await DockAccessoryManager.shared.setSystemTrackingEnabled(true)

// Disable system tracking for custom control
try await DockAccessoryManager.shared.setSystemTrackingEnabled(false)

System tracking state does not persist across app termination, reboots, or background/foreground transitions. Set it explicitly whenever the app needs a specific value.

Tap to Select Subject

Allow users to select a specific subject by tapping:

// Select the subject at a unit point in video-frame coordinates
try await accessory.selectSubject(at: CGPoint(x: 0.5, y: 0.5))

// Select specific subjects by identifier
try await accessory.selectSubjects([subjectUUID])

// Clear selection (return to automatic selection)
try await accessory.selectSubjects([])

Custom Tracking

Disable system tracking and provide your own observations when using custom ML models or the Vision framework.

Providing Observations

Construct DockAccessory.Observation values from your inference output and pass them to the accessory at 10-30 fps:

import DockKit
import AVFoundation

func processFrame(
    _ sampleBuffer: CMSampleBuffer,
    accessory: DockAccessory,
    activeDevice: AVCaptureDevice
) async throws {
    let cameraInfo = DockAccessory.CameraInformation(
        captureDevice: activeDevice.deviceType,
        cameraPosition: activeDevice.position,
        orientation: .corrected,
        cameraIntrinsics: frameIntrinsics(from: sampleBuffer),
        referenceDimensions: frameDimensions(from: sampleBuffer)
    )

    let detection = try await detector.detect(sampleBuffer)
    let observationType: DockAccessory.Observation.ObservationType = switch detection.kind {
    case .face: .humanFace
    case .body: .humanBody
    case .object: .object
    }

    let observation = DockAccessory.Observation(
        identifier: detection.id,
        type: observationType,
        rect: detection.rect,       // normalized, lower-left origin
        faceYawAngle: detection.faceYawAngle
    )

    try await accessory.track([observation], cameraInformation: cameraInfo)
}

Observation Types

When reviewing custom tracking, explicitly choose among the only supported ObservationType cases: .humanFace, .humanBody, and .object. Do not answer with only .humanFace when body or object detections are possible.

The rect uses normalized coordinates with a lower-left origin (same coordinate system as Vision framework -- no conversion needed).

Camera Information

DockAccessory.CameraInformation describes the active camera; do not hardcode placeholder device, intrinsics, or frame-size values. Set orientation to .corrected when coordinates are already relative to the bottom-left corner. In review answers, reject opaque optional cameraInfo placeholders and show construction from the active AVCaptureDevice plus the current CMSampleBuffer.

Track variants also accept [AVMetadataObject] instead of observations. Use the image: CVPixelBuffer overloads when DockKit should combine observations or metadata with the captured image buffer; the image argument is required in those overloads.

Framing and Region of Interest

Framing Modes

Control how the system frames tracked subjects:

try await accessory.setFramingMode(.automatic) // documented default
try await accessory.setFramingMode(.center)    // explicit opt-in
ModeBehavior
.automaticDocumented default; system decides optimal framing
.centerExplicit opt-in mode to keep subject centered
.leftFrame subject in left third
.rightFrame subject in right third

Default system behavior often centers the primary subject, but .center is never the default-like mode; .automatic is. Use .left or .right when graphic overlays occupy part of the frame.

Region of Interest

Constrain tracking to a specific area of the video frame:

// Normalized coordinates, origin at upper-left
let squareRegion = CGRect(x: 0.25, y: 0.0, width: 0.5, height: 1.0)
try await accessory.setRegionOfInterest(squareRegion)

Use region of interest when cropping to a non-standard aspect ratio (e.g., square video for conferencing) so subjects stay within the visible area.

Motor Control

Disable system tracking before controlling motors directly.

Angular Velocity

Set continuous rotation speed in radians per second:

import Spatial

// Pan right at 0.2 rad/s, tilt down at 0.1 rad/s
let velocity = Vector3D(x: 0.1, y: 0.2, z: 0.0)
try await accessory.setAngularVelocity(velocity)

// Stop all motion
try await accessory.setAngularVelocity(Vector3D())

Axes:

  • x -- pitch (tilt). Positive tilts down on iOS.
  • y -- yaw (pan). Positive pans right.
  • z -- roll (if supported by hardware).

Set Orientation

Move to a specific position over a duration:

let target = Vector3D(x: 0.0, y: 0.5, z: 0.0)  // Yaw 0.5 rad
let progress = try accessory.setOrientation(
    target,
    duration: .seconds(2),
    relative: false
)

Also accepts Rotation3D for quaternion-based orientation. Set relative: true to move relative to the current position. The returned Progress object tracks completion.

Motion State

Monitor the accessory's current position and velocity:

for await state in try accessory.motionStates {
    let positions = state.angularPositions   // Vector3D
    let velocities = state.angularVelocities // Vector3D
    let time = state.timestamp
    if let error = state.error {
        // Motor error occurred
    }
}

Setting Limits

Restrict range of motion and maximum speed per axis:

let yawLimit = try DockAccessory.Limits.Limit(
    positionRange: -1.0 ..< 1.0,   // radians
    maximumSpeed: 0.5               // rad/s
)
let limits = DockAccessory.Limits(yaw: yawLimit, pitch: nil, roll: nil)
try accessory.setLimits(limits)

Animations

Built-in character animations that move the dock expressively:

// Disable system tracking before animating
try await DockAccessoryManager.shared.setSystemTrackingEnabled(false)

let progress = try await accessory.animate(motion: .kapow)

// Wait for completion
while !progress.isFinished && !progress.isCancelled {
    try await Task.sleep(for: .milliseconds(100))
}

// Restore system tracking
try await DockAccessoryManager.shared.setSystemTrackingEnabled(true)
AnimationEffect
.yesNodding motion
.noShaking motion
.wakeupStartup-style motion
.kapowDramatic pendulum swing

Animations start from the accessory's current position and execute asynchronously. Always restore tracking state after completion. Keep animate(motion:) and setOrientation(_:duration:relative:) calls to no more than twice per second; higher call rates can throw .frameRateTooHigh.

Tracking State and Subject Selection

iOS 18+ exposes ML-derived tracking signals through the throwing trackingStates async sequence. Each state has time and trackedSubjects (.person or .object); persons include identifier, rect, speakingConfidence, lookingAtCameraConfidence, and saliencyRank (lower rank is more salient).

if #available(iOS 18.0, *) {
    for await state in try accessory.trackingStates {
        var speaker: UUID?
        var engaged: UUID?
        var salient: (id: UUID, rank: Int)?
        for subject in state.trackedSubjects {
            switch subject {
            case .person(let person):
                let id = person.identifier, rect = person.rect
                let speaking = person.speakingConfidence
                let looking = person.lookingAtCameraConfidence
                let rank = person.saliencyRank
                updateSubjectOverlay(id: id, rect: rect)
                if let speaking, speaking > 0.7 { speaker = id }
                if let looking, looking > 0.7 { engaged = id }
                if let rank, salient == nil || rank < salient!.rank { salient = (id, rank) }
            case .object(let object):
                let id = object.identifier, rect = object.rect
                let rank = object.saliencyRank
                updateSubjectOverlay(id: id, rect: rect)
                if let rank, salient == nil || rank < salient!.rank { salient = (id, rank) }
            }
        }
        if let id = speaker ?? engaged ?? salient?.id { try await accessory.selectSubjects([id]) }
    }
}

Use selectSubjects(_:) to lock tracking by UUID; pass [] to return to automatic selection. Use speakingConfidence for speakers, lookingAtCameraConfidence for engagement, rect for overlays, and lower saliencyRank values as fallback. In review answers, consume lookingAtCameraConfidence and rect in code, not just prose.

Accessory Events

Physical buttons on the dock trigger events through the throwing accessoryEvents async sequence (iOS 17.4+):

if #available(iOS 17.4, *) {
    for await event in try accessory.accessoryEvents {
        switch event {
        case .cameraShutter: break
        case .cameraFlip: break
        case .cameraZoom(factor: let factor): break
        case .button(id: let id, pressed: let pressed): break
        @unknown default: break
        }
    }
}

Third-party apps receive these events and implement behavior through AVFoundation.

Battery Monitoring

Monitor the dock's battery status through the throwing batteryStates async sequence (iOS 18+). A dock can report multiple batteries, each identified by name:

if #available(iOS 18.0, *) {
    var batteryRows: [String: (Double, DockAccessory.BatteryChargeState, Bool)] = [:]
    for await battery in try accessory.batteryStates {
        batteryRows[battery.name] = (battery.batteryLevel, battery.chargeState, battery.lowBattery)
    }
}

Common Mistakes

DON'T: Control motors without disabling system tracking

// WRONG -- system tracking fights manual commands
try await accessory.setAngularVelocity(velocity)

// CORRECT -- disable system tracking first
try await DockAccessoryManager.shared.setSystemTrackingEnabled(false)
try await accessory.setAngularVelocity(velocity)

DON'T: Assume tracking state persists across lifecycle events

// WRONG -- state may have reset after backgrounding
func applicationDidBecomeActive() {
    // Assume custom tracking is still active
}

// CORRECT -- re-set tracking state on foreground
func applicationDidBecomeActive() {
    Task {
        try await DockAccessoryManager.shared.setSystemTrackingEnabled(false)
    }
}

DON'T: Call track() outside the recommended rate

// WRONG -- calling once per second is too slow
try await accessory.track(observations, cameraInformation: cameraInfo)
// (called at 1 fps)

// CORRECT -- call at 10-30 fps
// Hook into AVCaptureVideoDataOutputSampleBufferDelegate for per-frame calls

DON'T: Spam orientation or animation calls

DockKit can throw .frameRateTooHigh if animate(motion:) or setOrientation(_:duration:relative:) is called more than twice per second. Set a trajectory, observe its Progress, and avoid tight command loops.

DON'T: Forget to restore tracking after animations

// WRONG -- tracking stays disabled after animation
try await DockAccessoryManager.shared.setSystemTrackingEnabled(false)
let progress = try await accessory.animate(motion: .kapow)

// CORRECT -- restore tracking when animation completes
try await DockAccessoryManager.shared.setSystemTrackingEnabled(false)
let progress = try await accessory.animate(motion: .kapow)
while !progress.isFinished && !progress.isCancelled {
    try await Task.sleep(for: .milliseconds(100))
}
try await DockAccessoryManager.shared.setSystemTrackingEnabled(true)

DON'T: Use DockKit in Simulator

DockKit requires a physical DockKit-compatible accessory. Guard initialization and provide fallback behavior when no accessory is available.

Review Checklist

  • import DockKit present where needed
  • Subscribed to accessoryStateChanges to detect dock/undock events
  • Handled both .docked and .undocked states
  • System tracking disabled before custom tracking or motor control
  • System tracking restored after animations complete
  • Custom observations supplied at 10-30 fps
  • animate and setOrientation commands limited to 2 calls per second
  • Observation rect uses normalized coordinates (lower-left origin)
  • Camera information is built inline from the active AVCaptureDevice and current sample buffer
  • Observation type choice names .humanFace, .humanBody, and .object
  • @unknown default handled in all switch statements over DockKit enums
  • Motion limits set if restricting accessory range of motion
  • Tracking state re-applied after app returns to foreground
  • accessoryEvents guarded with #available(iOS 17.4, *)
  • trackingStates and batteryStates guarded with #available(iOS 18.0, *)
  • Battery UI preserves BatteryState.name for multi-battery docks
  • No DockKit code paths executed in Simulator builds

References

FAQ

What does the dockkit skill do?

Control motorized camera docks and enable intelligent subject tracking using DockKit. Use when discovering DockKit-compatible accessories, implementing camera subject tracking for faces or bodies, controlling dock motors for pan and tilt, configuring framing behavior, setting regions of interest, or building video apps with automatic camera tracking.

How do I install dockkit?

Run npx skills add https://github.com/dpearson2699/swift-ios-skills --skill dockkit in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/dockkit/ (personal) or .claude/skills/dockkit/ (project).

Which AI agents can use dockkit?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is dockkit safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains dockkit?

It is published by dpearson2699 in dpearson2699/swift-ios-skills. It has 3,058 recorded installs.

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