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Core Motion

CommunityPopular
dpearson2699
core-motion

Access Core Motion accelerometer, gyroscope, magnetometer, device-motion, pedometer, activity-recognition, altitude, headphone motion, batched high-frequency workout motion, and water-submersion/depth data. Use when reading device sensors, counting steps, detecting walking/running/driving/cycling, tracking altitude, building motion interactions, handling AirPods head tracking, or implementing watchOS dive/depth features.

Overview

Publisherdpearson2699
Repositoryswift-ios-skills
Skill namecore-motion
Stars
1.2K
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Bundled files
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  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by dpearson2699 on GitHub. Read the source before you install it.

Installation

Install the Core Motion AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dpearson2699/swift-ios-skills/tree/main/skills/core-motion
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dpearson2699/swift-ios-skills.git /tmp/swift-ios-skills
mkdir -p .claude/skills
cp -r /tmp/swift-ios-skills/skills/core-motion .claude/skills/core-motion
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Core Motion in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Core Motion on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Core Motion is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CoreMotion

Read device motion, pedometer/activity, altitude, headphone, batched-workout, and submersion sensors with Core Motion. Scope: Swift 6.3, iOS 26+.

Contents

Setup

Info.plist

Add NSMotionUsageDescription to Info.plist with a user-facing string explaining why your app needs motion data. Without this key, the app crashes on first access.

xml
<key>NSMotionUsageDescription</key>
<string>This app uses motion data to track your activity.</string>

Authorization

Use the matching manager's authorizationStatus() or authorizationStatus property when an API exposes one (CMPedometer, CMMotionActivityManager, CMAltimeter, headphone motion, batched sensors, and submersion). Raw CMMotionManager accelerometer/gyro/device-motion streams have no explicit authorization request API; still ship the usage string and handle errors from start/update callbacks.

swift
import CoreMotion

let status = CMMotionActivityManager.authorizationStatus()
switch status {
case .notDetermined:
    // Will prompt on first use
    break
case .authorized:
    break
case .restricted, .denied:
    // Direct user to Settings
    break
@unknown default:
    break
}

CMMotionManager: Sensor Data

Create exactly one CMMotionManager per app. Multiple instances degrade sensor update rates.

swift
import CoreMotion

let motionManager = CMMotionManager()

Accelerometer Updates

swift
guard motionManager.isAccelerometerAvailable else { return }

motionManager.accelerometerUpdateInterval = 1.0 / 60.0  // 60 Hz

motionManager.startAccelerometerUpdates(to: .main) { data, error in
    guard let acceleration = data?.acceleration else { return }
    print("x: \(acceleration.x), y: \(acceleration.y), z: \(acceleration.z)")
}

// When done:
motionManager.stopAccelerometerUpdates()

Gyroscope Updates

swift
guard motionManager.isGyroAvailable else { return }

motionManager.gyroUpdateInterval = 1.0 / 60.0

motionManager.startGyroUpdates(to: .main) { data, error in
    guard let rotationRate = data?.rotationRate else { return }
    print("x: \(rotationRate.x), y: \(rotationRate.y), z: \(rotationRate.z)")
}

motionManager.stopGyroUpdates()

Polling Pattern (Games)

For games, start updates without a handler and poll the latest sample each frame:

swift
motionManager.startAccelerometerUpdates()

// In your game loop / display link:
if let data = motionManager.accelerometerData {
    let tilt = data.acceleration.x
    // Move player based on tilt
}

Processed Device Motion

Device motion fuses accelerometer, gyroscope, and magnetometer into a single CMDeviceMotion object with attitude, user acceleration (gravity removed), rotation rate, and calibrated magnetic field.

When giving device-motion guidance, show the runtime frame check in the snippet instead of hard-coding a corrected, magnetic-north, or true-north frame. Fall back to .xArbitraryZVertical when the preferred frame is unavailable.

swift
guard motionManager.isDeviceMotionAvailable else { return }

let availableFrames = CMMotionManager.availableAttitudeReferenceFrames()
let frame: CMAttitudeReferenceFrame = availableFrames.contains(.xArbitraryCorrectedZVertical)
    ? .xArbitraryCorrectedZVertical
    : .xArbitraryZVertical

motionManager.deviceMotionUpdateInterval = 1.0 / 60.0

motionManager.startDeviceMotionUpdates(
    using: frame,
    to: .main
) { motion, error in
    guard let motion else { return }

    let attitude = motion.attitude       // roll, pitch, yaw
    let userAccel = motion.userAcceleration
    let gravity = motion.gravity
    let heading = motion.heading         // degrees relative to the current frame

    print("Pitch: \(attitude.pitch), Roll: \(attitude.roll)")
}

motionManager.stopDeviceMotionUpdates()

Attitude Reference Frames

For simple tilt controls, use .xArbitraryZVertical or .xArbitraryCorrectedZVertical; they avoid magnetometer/location dependencies. Before requesting corrected, magnetic-north, or true-north frames, call CMMotionManager.availableAttitudeReferenceFrames() and fall back to an available frame.

FrameUse Case
.xArbitraryZVerticalDefault. Z is vertical, X arbitrary at start. Most games.
.xArbitraryCorrectedZVerticalSame as above, corrected for gyro drift over time.
.xMagneticNorthZVerticalX points to magnetic north. Requires magnetometer.
.xTrueNorthZVerticalX points to true north. Requires magnetometer + location.

Check available frames before use:

swift
let available = CMMotionManager.availableAttitudeReferenceFrames()
if available.contains(.xTrueNorthZVertical) {
    // Safe to use true north
}

CMPedometer: Step and Distance Data

CMPedometer provides step counts, distance, pace, cadence, and floor counts.

swift
let pedometer = CMPedometer()

guard CMPedometer.isStepCountingAvailable() else { return }

// Historical query
pedometer.queryPedometerData(
    from: Calendar.current.startOfDay(for: Date()),
    to: Date()
) { data, error in
    guard let data else { return }
    print("Steps today: \(data.numberOfSteps)")
    print("Distance: \(data.distance?.doubleValue ?? 0) meters")
    print("Floors up: \(data.floorsAscended?.intValue ?? 0)")
}

// Live updates
pedometer.startUpdates(from: Date()) { data, error in
    guard let data else { return }
    print("Steps: \(data.numberOfSteps)")
}

// Stop when done
pedometer.stopUpdates()

Availability Checks

MethodWhat It Checks
isStepCountingAvailable()Step counter hardware
isDistanceAvailable()Distance estimation
isFloorCountingAvailable()Barometric altimeter for floors
isPaceAvailable()Pace data
isCadenceAvailable()Cadence data

CMMotionActivityManager: Activity Recognition

Detects whether the user is stationary, walking, running, cycling, or in a vehicle.

swift
let activityManager = CMMotionActivityManager()

guard CMMotionActivityManager.isActivityAvailable() else { return }

// Live activity updates
activityManager.startActivityUpdates(to: .main) { activity in
    guard let activity else { return }

    if activity.walking {
        print("Walking (confidence: \(activity.confidence.rawValue))")
    } else if activity.running {
        print("Running")
    } else if activity.automotive {
        print("In vehicle")
    } else if activity.cycling {
        print("Cycling")
    } else if activity.stationary {
        print("Stationary")
    }
}

activityManager.stopActivityUpdates()

Historical Activity Query

swift
let yesterday = Calendar.current.date(byAdding: .day, value: -1, to: Date())!

activityManager.queryActivityStarting(
    from: yesterday,
    to: Date(),
    to: .main
) { activities, error in
    guard let activities else { return }
    for activity in activities {
        print("\(activity.startDate): walking=\(activity.walking)")
    }
}

CMAltimeter: Altitude Data

Altimeter access is covered by NSMotionUsageDescription; handle denied motion access through unavailable data and update-handler errors.

swift
let altimeter = CMAltimeter()

guard CMAltimeter.isRelativeAltitudeAvailable() else { return }

altimeter.startRelativeAltitudeUpdates(to: .main) { data, error in
    guard let data else { return }
    print("Relative altitude: \(data.relativeAltitude) meters")
    print("Pressure: \(data.pressure) kPa")
}

altimeter.stopRelativeAltitudeUpdates()

Absolute altitude is altitude relative to sea level, not GPS-based altitude. First check availability. Absolute altitude is available only on supported hardware such as iPhone 12 or later and Apple Watch Series 6, Apple Watch SE, or later.

swift
guard CMAltimeter.isAbsoluteAltitudeAvailable() else { return }

altimeter.startAbsoluteAltitudeUpdates(to: .main) { data, error in
    guard let data else { return }
    print("Altitude: \(data.altitude)m, accuracy: \(data.accuracy)m")
}

altimeter.stopAbsoluteAltitudeUpdates()

Update Intervals and Battery

IntervalHzUse CaseBattery Impact
1.0 / 10.010UI orientationLow
1.0 / 30.030Casual gamesModerate
1.0 / 60.060Action gamesHigh
1.0 / 100.0100Max rate (iPhone)Very High

Use the lowest frequency that meets your needs. Do not assume a fixed maximum sample rate across devices. For high-frequency workout motion, use CMBatchedSensorManager where supported and read its reported accelerometerDataFrequency or deviceMotionDataFrequency instead of assigning those read-only properties.

Common Mistakes

DON'T: Create multiple CMMotionManager instances

Retain one app-level CMMotionManager; competing instances can reduce update rates.

DON'T: Skip sensor availability checks

Apply the matching is...Available gate immediately before starting each sensor stream.

DON'T: Forget to stop updates

Pair every start with the matching stop in the counterpart lifecycle or task cancellation path.

DON'T: Use unnecessarily high update rates

Choose the lowest rate that meets the interaction and use the Update Intervals and Battery table as a starting point.

DON'T: Assume all CMMotionActivity properties are mutually exclusive

swift
// WRONG -- checking only one property
if activity.walking { handleWalking() }

// CORRECT -- multiple can be true simultaneously; check confidence
if activity.walking && activity.confidence == .high {
    handleWalking()
} else if activity.automotive && activity.confidence != .low {
    handleDriving()
}

Review Checklist

  • NSMotionUsageDescription present in Info.plist with a clear explanation
  • Single CMMotionManager instance shared across the app
  • Sensor availability checked before starting updates (isAccelerometerAvailable, etc.)
  • Authorization status checked before pedometer/activity APIs
  • Update interval set to the lowest acceptable frequency
  • All start*Updates calls have matching stop*Updates in lifecycle counterparts
  • Handlers dispatched to appropriate queues (not blocking main for heavy processing)
  • CMMotionActivity.confidence checked before acting on activity type
  • Error parameters checked in update handlers
  • Device-motion snippets call CMMotionManager.availableAttitudeReferenceFrames() before requesting a specific attitude frame
  • Attitude reference frame chosen based on actual need (not defaulting to true north unnecessarily)

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Core Motion AI skill do?

Access Core Motion accelerometer, gyroscope, magnetometer, device-motion, pedometer, activity-recognition, altitude, headphone motion, batched high-frequency workout motion, and water-submersion/depth data. Use when reading device sensors, counting steps, detecting walking/running/driving/cycling, tracking altitude, building motion interactions, handling AirPods head tracking, or implementing watchOS dive/depth features.

Why use Core Motion on TypingMind?

Because you install it once and use it with any model. Core Motion is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Core Motion in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dpearson2699/swift-ios-skills/tree/main/skills/core-motion. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Core Motion?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Core Motion?

As many as you like. As long as a model supports skills, you can use Core Motion with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Core Motion AI skill free?

It is published on GitHub by dpearson2699. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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