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Mapbox Android Patterns

Organization
mapbox
mapbox-android-patterns

Official integration patterns for Mapbox Maps SDK on Android. Covers installation, adding markers, user location, custom data, styles, camera control, and featureset interactions. Based on official Mapbox documentation.

Overview

Publishermapbox
Repositorymapbox-agent-skills
Skill namemapbox-android-patterns
Stars
78
Forks
17
Bundled files
8
LicenseMIT
Links
  • 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.

  • 8 bundled files

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

  • Open source

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

Installation

Install the Mapbox Android Patterns 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.
  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/mapbox/mapbox-agent-skills.git /tmp/mapbox-agent-skills
mkdir -p .claude/skills
cp -r /tmp/mapbox-agent-skills/skills/mapbox-android-patterns .claude/skills/mapbox-android-patterns
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mapbox Android Patterns 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 Mapbox Android Patterns 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 Mapbox Android Patterns 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.

Mapbox Android Integration Patterns

Official patterns for integrating Mapbox Maps SDK v11 on Android with Kotlin, Jetpack Compose, and View system.

Use this skill when:

  • Installing and configuring Mapbox Maps SDK for Android
  • Adding markers and annotations to maps
  • Showing user location and tracking with camera
  • Adding custom data (GeoJSON) to maps
  • Working with map styles, camera, or user interaction
  • Handling feature interactions and taps

Official Resources:


Installation & Setup

Requirements

  • Android SDK 21+
  • Kotlin or Java
  • Android Studio
  • Free Mapbox account

Step 1: Configure Access Token

Create app/res/values/mapbox_access_token.xml:

xml
<?xml version="1.0" encoding="utf-8"?>
<resources xmlns:tools="http://schemas.android.com/tools">
    <string name="mapbox_access_token" translatable="false"
        tools:ignore="UnusedResources">YOUR_MAPBOX_ACCESS_TOKEN</string>
</resources>

Get your token: Sign in at mapbox.com

Step 1b: Internet permission (required)

Maps need network access. Include this in AndroidManifest.xml — agents often omit it and only list location permissions later:

xml
<uses-permission android:name="android.permission.INTERNET" />

Step 2: Add Maven Repository

In settings.gradle.kts:

kotlin
dependencyResolutionManagement {
    repositories {
        google()
        mavenCentral()
        maven {
            url = uri("https://api.mapbox.com/downloads/v2/releases/maven")
        }
    }
}

Step 3: Add Dependency

In module build.gradle.kts:

kotlin
android {
    defaultConfig {
        minSdk = 21
    }
}

dependencies {
    implementation("com.mapbox.maps:android:11.18.1")
}

For Jetpack Compose:

kotlin
dependencies {
    implementation("com.mapbox.maps:android:11.18.1")
    implementation("com.mapbox.extension:maps-compose:11.18.1")
}

Map Initialization

Jetpack Compose Pattern

Basic map:

kotlin
import androidx.compose.runtime.*
import androidx.compose.foundation.layout.fillMaxSize
import androidx.compose.ui.Modifier
import com.mapbox.maps.extension.compose.*
import com.mapbox.maps.Style
import com.mapbox.geojson.Point

@Composable
fun MapScreen() {
    MapboxMap(
        modifier = Modifier.fillMaxSize()
    ) {
        // Initialize camera via MapEffect (Style.STANDARD loads by default)
        MapEffect(Unit) { mapView ->
            // Set initial camera position
            mapView.mapboxMap.setCamera(
                CameraOptions.Builder()
                    .center(Point.fromLngLat(-122.4194, 37.7749))
                    .zoom(12.0)
                    .build()
            )
        }
    }
}

With ornaments:

kotlin
MapboxMap(
    modifier = Modifier.fillMaxSize(),
    scaleBar = {
        ScaleBar(
            enabled = true,
            position = Alignment.BottomStart
        )
    },
    compass = {
        Compass(enabled = true)
    }
) {
    // Style.STANDARD loads by default
}

View System Pattern

Layout XML (activity_map.xml):

xml
<?xml version="1.0" encoding="utf-8"?>
<androidx.constraintlayout.widget.ConstraintLayout
    xmlns:android="http://schemas.android.com/apk/res/android"
    android:layout_width="match_parent"
    android:layout_height="match_parent">

    <com.mapbox.maps.MapView
        android:id="@+id/mapView"
        android:layout_width="match_parent"
        android:layout_height="match_parent" />

</androidx.constraintlayout.widget.ConstraintLayout>

Activity:

kotlin
import android.os.Bundle
import androidx.appcompat.app.AppCompatActivity
import com.mapbox.maps.MapView
import com.mapbox.maps.Style
import com.mapbox.geojson.Point

class MapActivity : AppCompatActivity() {
    private lateinit var mapView: MapView

    override fun onCreate(savedInstanceState: Bundle?) {
        super.onCreate(savedInstanceState)
        setContentView(R.layout.activity_map)

        mapView = findViewById(R.id.mapView)

        mapView.mapboxMap.setCamera(
            CameraOptions.Builder()
                .center(Point.fromLngLat(-122.4194, 37.7749))
                .zoom(12.0)
                .build()
        )

        mapView.mapboxMap.loadStyle(Style.STANDARD)
    }

    override fun onStart() {
        super.onStart()
        mapView.onStart()
    }

    override fun onStop() {
        super.onStop()
        mapView.onStop()
    }

    override fun onDestroy() {
        super.onDestroy()
        mapView.onDestroy()
    }
}

Add Markers (Point Annotations)

Point annotations are the most common way to mark locations on the map.

Jetpack Compose:

kotlin
MapboxMap(modifier = Modifier.fillMaxSize()) {
    MapEffect(Unit) { mapView ->
        // Load style first
        mapView.mapboxMap.loadStyle(Style.STANDARD)

        // Create annotation manager and add markers
        val annotationManager = mapView.annotations.createPointAnnotationManager()
        val pointAnnotation = PointAnnotationOptions()
            .withPoint(Point.fromLngLat(-122.4194, 37.7749))
            .withIconImage("custom-marker")
        annotationManager.create(pointAnnotation)
    }
}

// Note: Compose doesn't have declarative PointAnnotation component
// Markers must be added imperatively via MapEffect

View System:

kotlin
// Create annotation manager (once, reuse for updates)
val pointAnnotationManager = mapView.annotations.createPointAnnotationManager()

// Create marker
val pointAnnotation = PointAnnotationOptions()
    .withPoint(Point.fromLngLat(-122.4194, 37.7749))
    .withIconImage("custom-marker")

pointAnnotationManager.create(pointAnnotation)

Multiple markers:

kotlin
val locations = listOf(
    Point.fromLngLat(-122.4194, 37.7749),
    Point.fromLngLat(-122.4094, 37.7849),
    Point.fromLngLat(-122.4294, 37.7649)
)

val annotations = locations.map { point ->
    PointAnnotationOptions()
        .withPoint(point)
        .withIconImage("marker")
}

pointAnnotationManager.create(annotations)

Show User Location (Display)

Step 1: Add permissions to AndroidManifest.xml:

xml
<uses-permission android:name="android.permission.INTERNET" />
<uses-permission android:name="android.permission.ACCESS_FINE_LOCATION" />
<uses-permission android:name="android.permission.ACCESS_COARSE_LOCATION" />

Step 2: Request permissions and show location:

kotlin
// Request permissions first (use ActivityResultContracts)

// Show location puck
mapView.location.updateSettings {
    enabled = true
    puckBearingEnabled = true
}

Performance Best Practices

Reuse Annotation Managers

kotlin
// Don't create new managers repeatedly
// val manager = mapView.annotations.createPointAnnotationManager() // each call

// Create once, reuse
val pointAnnotationManager = mapView.annotations.createPointAnnotationManager()

fun updateMarkers() {
    pointAnnotationManager.deleteAll()
    pointAnnotationManager.create(markers)
}

Batch Annotation Updates

kotlin
// Create all at once
pointAnnotationManager.create(allAnnotations)

// Don't create one by one in a loop

Lifecycle Management

kotlin
// Always call lifecycle methods
override fun onStart() {
    super.onStart()
    mapView.onStart()
}

override fun onStop() {
    super.onStop()
    mapView.onStop()
}

override fun onDestroy() {
    super.onDestroy()
    mapView.onDestroy()
}

Use Standard Style

kotlin
// Standard style is optimized and recommended
Style.STANDARD

// Use other styles only when needed for specific use cases
Style.STANDARD_SATELLITE // Satellite imagery

Troubleshooting

Map Not Displaying

Check:

  1. Token in mapbox_access_token.xml
  2. Token is valid (test at mapbox.com)
  3. Maven repository configured
  4. Dependency added correctly
  5. Internet permission in manifest

Style Not Loading

kotlin
mapView.mapboxMap.subscribeStyleLoaded { _ ->
    Log.d("Map", "Style loaded successfully")
    // Add layers and sources here
}

Performance Issues

  • Use Style.STANDARD (recommended and optimized)
  • Limit visible annotations to viewport
  • Reuse annotation managers
  • Avoid frequent style reloads
  • Call lifecycle methods (onStart, onStop, onDestroy)
  • Batch annotation updates

Reference Files

Load these references when you need detailed patterns for specific topics:

  • references/compose.md -- Jetpack Compose: dependencies, token setup, MapboxMap, annotations with click, GeoJSON, MapEffect
  • references/annotations.md -- Circle, Polyline, and Polygon annotation patterns
  • references/location-tracking.md -- Camera follow user location + get current location once
  • references/custom-data.md -- GeoJSON sources and layers: lines, polygons, points, update/remove
  • references/camera-styles.md -- Camera control (set, animate, fit) + map styles (built-in and custom)
  • references/interactions.md -- Featureset interactions, custom layer taps, long press, gestures

Additional Resources

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 Mapbox Android Patterns AI skill do?

Official integration patterns for Mapbox Maps SDK on Android. Covers installation, adding markers, user location, custom data, styles, camera control, and featureset interactions. Based on official Mapbox documentation.

Why use Mapbox Android Patterns on TypingMind?

Because you install it once and use it with any model. Mapbox Android Patterns 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 Mapbox Android Patterns in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mapbox/mapbox-agent-skills/tree/main/skills/mapbox-android-patterns. 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 Mapbox Android Patterns?

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 Mapbox Android Patterns?

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

Is the Mapbox Android Patterns AI skill free?

Yes. It is published on GitHub by mapbox under the MIT license. 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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