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Healthkit

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dpearson2699
healthkit

Read, write, and query Apple Health data using HealthKit. Covers HKHealthStore authorization, sample queries, statistics queries, statistics collection queries for charts, saving HKQuantitySample data, background delivery, workout sessions with HKWorkoutSession and HKLiveWorkoutBuilder, HKUnit, and HKQuantityTypeIdentifier values. Use when integrating with Apple Health, displaying health metrics, recording workouts, or enabling background health data delivery.

Overview

Publisherdpearson2699
Repositoryswift-ios-skills
Skill namehealthkit
Stars
1.2K
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61
Bundled files
2
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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 Healthkit 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/healthkit
  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/healthkit .claude/skills/healthkit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Healthkit 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 Healthkit 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 Healthkit 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.

HealthKit

Read and write health and fitness data from the Apple Health store. Covers authorization, queries, writing samples, background delivery, and workout sessions. Targets Swift 6.3 / iOS 26+.

Contents

Setup and Availability

Project Configuration

  1. Enable the HealthKit capability in Xcode (adds the entitlement)
  2. Add NSHealthShareUsageDescription (read) and NSHealthUpdateUsageDescription (write) to Info.plist
  3. For background delivery, enable the "Background Delivery" sub-capability

Availability Check

Always check availability before calling other HealthKit APIs. Health data is available on iOS, watchOS, visionOS, iPadOS 17+, and iOS apps running on Vision Pro. It is unavailable on iPadOS 16 or earlier and may be restricted by managed device policy.

swift
import HealthKit

guard HKHealthStore.isHealthDataAvailable() else {
    // Health data is unavailable or restricted on this device.
    return
}

let healthStore = HKHealthStore()

Create a single HKHealthStore instance and reuse it throughout your app. It is thread-safe. If HealthKit is optional, review Xcode's generated UIRequiredDeviceCapabilities healthkit entry so unsupported devices are not excluded unintentionally.

Authorization

Request only the types your app genuinely needs. App Review rejects apps that over-request.

swift
func requestAuthorization() async throws {
    let typesToShare: Set<HKSampleType> = [
        HKQuantityType(.stepCount),
        HKQuantityType(.activeEnergyBurned)
    ]

    let typesToRead: Set<HKObjectType> = [
        HKQuantityType(.stepCount),
        HKQuantityType(.heartRate),
        HKQuantityType(.activeEnergyBurned),
        HKCharacteristicType(.dateOfBirth)
    ]

    try await healthStore.requestAuthorization(
        toShare: typesToShare,
        read: typesToRead
    )
}

Checking Authorization Status

authorizationStatus(for:) reports write/share authorization. HealthKit does not reveal whether read permission was granted or denied. If the user denies read access, queries return only samples your app successfully saved, which may look like empty or partial data.

swift
let status = healthStore.authorizationStatus(
    for: HKQuantityType(.stepCount)
)

switch status {
case .notDetermined:
    // Haven't requested yet -- safe to call requestAuthorization
    break
case .sharingAuthorized:
    // User granted write access
    break
case .sharingDenied:
    // User denied write access (read denial is indistinguishable from "no data")
    break
@unknown default:
    break
}

Reading Data: Sample Queries

Use HKSampleQueryDescriptor (async/await) for one-shot reads. Prefer descriptors over the older callback-based HKSampleQuery.

swift
func fetchRecentHeartRates() async throws -> [HKQuantitySample] {
    let heartRateType = HKQuantityType(.heartRate)

    let descriptor = HKSampleQueryDescriptor(
        predicates: [.quantitySample(type: heartRateType)],
        sortDescriptors: [SortDescriptor(\.endDate, order: .reverse)],
        limit: 20
    )

    let results = try await descriptor.result(for: healthStore)
    return results
}

// Extracting values from samples:
for sample in results {
    let bpm = sample.quantity.doubleValue(
        for: HKUnit.count().unitDivided(by: .minute())
    )
    print("\(bpm) bpm at \(sample.endDate)")
}

Reading Data: Statistics Queries

Use HKStatisticsQueryDescriptor for aggregated single-value stats (sum, average, min, max).

swift
func fetchTodayStepCount() async throws -> Double? {
    let calendar = Calendar.current
    let startOfDay = calendar.startOfDay(for: Date())
    let endOfDay = calendar.date(byAdding: .day, value: 1, to: startOfDay)!

    let predicate = HKQuery.predicateForSamples(
        withStart: startOfDay, end: endOfDay
    )
    let stepType = HKQuantityType(.stepCount)
    let samplePredicate = HKSamplePredicate.quantitySample(
        type: stepType, predicate: predicate
    )

    let query = HKStatisticsQueryDescriptor(
        predicate: samplePredicate,
        options: .cumulativeSum
    )

    let result = try await query.result(for: healthStore)
    return result?.sumQuantity()?.doubleValue(for: .count())
}

Options by data type:

  • Cumulative types (steps, calories): .cumulativeSum
  • Discrete types (heart rate, weight): .discreteAverage, .discreteMin, .discreteMax

Reading Data: Statistics Collection Queries

Use HKStatisticsCollectionQueryDescriptor for time-series data grouped into intervals -- ideal for charts.

swift
func fetchDailySteps(forLast days: Int) async throws -> [(date: Date, steps: Double)] {
    let calendar = Calendar.current
    let endDate = calendar.startOfDay(
        for: calendar.date(byAdding: .day, value: 1, to: Date())!
    )
    let startDate = calendar.date(byAdding: .day, value: -days, to: endDate)!

    let predicate = HKQuery.predicateForSamples(
        withStart: startDate, end: endDate
    )
    let stepType = HKQuantityType(.stepCount)
    let samplePredicate = HKSamplePredicate.quantitySample(
        type: stepType, predicate: predicate
    )

    let query = HKStatisticsCollectionQueryDescriptor(
        predicate: samplePredicate,
        options: .cumulativeSum,
        anchorDate: endDate,
        intervalComponents: DateComponents(day: 1)
    )

    let collection = try await query.result(for: healthStore)
    var dailySteps: [(date: Date, steps: Double)] = []

    collection.statisticsCollection.enumerateStatistics(
        from: startDate, to: endDate
    ) { statistics, _ in
        let steps = statistics.sumQuantity()?
            .doubleValue(for: .count()) ?? 0
        dailySteps.append((date: statistics.startDate, steps: steps))
    }

    return dailySteps
}

Long-Running Collection Query

Use results(for:) (plural) to get an AsyncSequence that emits updates as new data arrives:

swift
let updateStream = query.results(for: healthStore)

Task {
    for try await result in updateStream {
        // result.statisticsCollection contains updated data
    }
}

Writing Data

Create HKQuantitySample objects and save them to the store.

swift
func saveSteps(count: Double, start: Date, end: Date) async throws {
    let stepType = HKQuantityType(.stepCount)
    let quantity = HKQuantity(unit: .count(), doubleValue: count)

    let sample = HKQuantitySample(
        type: stepType,
        quantity: quantity,
        start: start,
        end: end
    )

    try await healthStore.save(sample)
}

Treat try await healthStore.save(sample) returning as the save success gate; only then report success or advance app state. On failure, surface the error and correct the known authorization, type, unit, duration, or input problem before constructing another sample. A bounded query or inspection in the Health app is useful as an integration-test check when persistence evidence is required, but is not a mandatory production read after every save.

Your app can only delete samples it created. Samples from other apps or Apple Watch are read-only.

Background Delivery

Register for background updates so your app is launched when new data arrives. Requires the background delivery entitlement.

swift
func enableStepCountBackgroundDelivery() async throws {
    let stepType = HKQuantityType(.stepCount)

    try await healthStore.enableBackgroundDelivery(
        for: stepType,
        frequency: .hourly
    )
}

Pair with an HKObserverQuery to handle notifications. Always call the completion handler:

swift
let observerQuery = HKObserverQuery(
    sampleType: HKQuantityType(.stepCount),
    predicate: nil
) { query, completionHandler, error in
    defer { completionHandler() }  // Must call to signal done
    guard error == nil else { return }
    // Fetch new data, update UI, etc.
}
healthStore.execute(observerQuery)

Frequencies: .immediate, .hourly, .daily, .weekly

Set up observer queries as soon as the app launches, then call enableBackgroundDelivery once for the same sample type. The system persists the registration, wakes the app at most once per requested frequency, and enforces tighter caps for some types such as hourly step-count delivery on iOS. Background delivery is not supported on Simulator; test it on device.

Workout Sessions

Use HKWorkoutSession and HKLiveWorkoutBuilder to track live workouts. HKWorkoutSession is available on iOS/iPadOS 17+, visionOS 1+, and watchOS 2+. HKLiveWorkoutBuilder is available on iOS/iPadOS 26+ and watchOS 5+, so gate live-builder code if supporting older iOS/iPadOS releases.

On iPhone and iPad, live heart-rate collection requires a paired external heart rate sensor. Apple Watch sessions can collect high-frequency heart-rate data. For locked iPhone workouts, plan for the system's workout-data access flow before showing health metrics on the Lock Screen.

swift
func startWorkout() async throws {
    let configuration = HKWorkoutConfiguration()
    configuration.activityType = .running
    configuration.locationType = .outdoor

    let session = try HKWorkoutSession(
        healthStore: healthStore,
        configuration: configuration
    )
    session.delegate = self

    let builder = session.associatedWorkoutBuilder()
    builder.dataSource = HKLiveWorkoutDataSource(
        healthStore: healthStore,
        workoutConfiguration: configuration
    )

    session.startActivity(with: Date())
    try await builder.beginCollection(at: Date())
}

// Request teardown; finalize from the delegate's .stopped transition.
session.stopActivity(with: Date())

Do not call endCollection and finishWorkout immediately after requesting the stop. Wait for the session delegate's .stopped transition, then await builder.endCollection(at:) followed by builder.finishWorkout(). Report the workout as saved and clear session state only after both operations return. Handle each thrown error without blindly repeating teardown. A successful finishWorkout() can return no workout object while the device is locked, so a nil result alone is not failure.

For full workout lifecycle management including pause/resume, delegate handling, and multi-device mirroring, see references/healthkit-patterns.md.

Common Data Types

HKQuantityTypeIdentifier

IdentifierCategoryUnit
.stepCountFitness.count()
.distanceWalkingRunningFitness.meter()
.activeEnergyBurnedFitness.kilocalorie()
.basalEnergyBurnedFitness.kilocalorie()
.heartRateVitals.count()/.minute()
.restingHeartRateVitals.count()/.minute()
.oxygenSaturationVitals.percent()
.bodyMassBody.gramUnit(with: .kilo)
.bodyMassIndexBody.count()
.heightBody.meter()
.bodyFatPercentageBody.percent()
.bloodGlucoseLab.gramUnit(with: .milli).unitDivided(by: .literUnit(with: .deci))

HKCategoryTypeIdentifier

Common category types: .sleepAnalysis, .mindfulSession, .appleStandHour

HKCharacteristicType

Read-only user characteristics include .dateOfBirth, .biologicalSex, .bloodType, .fitzpatrickSkinType, .wheelchairUse, and .activityMoveMode.

HKUnit Reference

swift
// Basic units
HKUnit.count()                              // Steps, counts
HKUnit.meter()                              // Distance
HKUnit.mile()                               // Distance (imperial)
HKUnit.kilocalorie()                        // Energy
HKUnit.joule(with: .kilo)                   // Energy (SI)
HKUnit.gramUnit(with: .kilo)                // Mass (kg)
HKUnit.pound()                              // Mass (imperial)
HKUnit.percent()                            // Percentage

// Compound units
HKUnit.count().unitDivided(by: .minute())   // Heart rate (bpm)
HKUnit.meter().unitDivided(by: .second())   // Speed (m/s)

// Prefixed units
HKUnit.gramUnit(with: .milli)               // Milligrams
HKUnit.literUnit(with: .deci)               // Deciliters

Common Mistakes

  1. Over-requesting data types. Request only the read/write types the feature actually uses; broad HealthKit permission sheets are an App Review risk.
  2. Treating read authorization like write authorization. You can check .sharingAuthorized before saving, but read denial is privacy-protected and looks like app-owned-only, empty, or partial results.
  3. Skipping isHealthDataAvailable(). Check before HealthKit access and handle unavailable or restricted stores without crashing.
  4. Using callback queries for new async code. Prefer async descriptors for one-shot reads and statistics, and keep broad queries off the main actor.
  5. Forgetting observer completion handlers. Always call the handler; missed completions can delay or stop future background deliveries.
  6. Assuming .immediate means immediate. Background delivery is capped by the system and must be tested on device.
  7. Using cumulative stats for discrete values. Match statistics options to the data type: cumulative sums for steps/energy, discrete average/min/max for heart rate, weight, and similar samples.

Review Checklist

  • HKHealthStore.isHealthDataAvailable() checked before any HealthKit access
  • Only necessary data types requested in authorization
  • Info.plist includes NSHealthShareUsageDescription and/or NSHealthUpdateUsageDescription
  • HealthKit capability enabled in Xcode project
  • Write authorization checked before saving; read denial handled as partial or empty query results
  • Single HKHealthStore instance reused (not created per query)
  • Async query descriptors used instead of callback-based queries
  • Heavy queries not blocking main thread
  • Statistics options match data type (cumulative vs. discrete)
  • Background delivery paired with app-launch HKObserverQuery setup and completionHandler called
  • Background delivery entitlement enabled if using enableBackgroundDelivery
  • Background delivery tested on device and frequency caps considered
  • Workout stop waits for the delegate's .stopped transition before endCollection and finishWorkout; state clears only after successful finalization
  • Workout API availability and live heart-rate sensor requirements handled
  • Delete operations target only objects the app previously saved

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 Healthkit AI skill do?

Read, write, and query Apple Health data using HealthKit. Covers HKHealthStore authorization, sample queries, statistics queries, statistics collection queries for charts, saving HKQuantitySample data, background delivery, workout sessions with HKWorkoutSession and HKLiveWorkoutBuilder, HKUnit, and HKQuantityTypeIdentifier values. Use when integrating with Apple Health, displaying health metrics, recording workouts, or enabling background health data delivery.

Why use Healthkit on TypingMind?

Because you install it once and use it with any model. Healthkit 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 Healthkit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dpearson2699/swift-ios-skills/tree/main/skills/healthkit. 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 Healthkit?

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 Healthkit?

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

Is the Healthkit 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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