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Android Jetpack Compose Expert

Community
kursku
android-jetpack-compose-expert

Expert guidance for building modern Android UIs with Jetpack Compose, covering state management, navigation, performance, and Material Design 3.

Overview

Publisherkursku
Repositoryskills
Skill nameandroid-jetpack-compose-expert
Stars
112
Forks
34
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Android Jetpack Compose Expert 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/kursku/skills/tree/master/packs/global-skillshare-import/wave-001/android-jetpack-compose-expert
  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/kursku/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/packs/global-skillshare-import/wave-001/android-jetpack-compose-expert .claude/skills/android-jetpack-compose-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Android Jetpack Compose Expert 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 Android Jetpack Compose Expert 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 Android Jetpack Compose Expert 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.

Android Jetpack Compose Expert

Overview

A comprehensive guide for building production-quality Android applications using Jetpack Compose. This skill covers architectural patterns, state management with ViewModels, navigation type-safety, and performance optimization techniques.

When to Use This Skill

  • Use when starting a new Android project with Jetpack Compose.
  • Use when migrating legacy XML layouts to Compose.
  • Use when implementing complex UI state management and side effects.
  • Use when optimizing Compose performance (recomposition counts, stability).
  • Use when setting up Navigation with type safety.

Step-by-Step Guide

1. Project Setup & Dependencies

Ensure your libs.versions.toml includes the necessary Compose BOM and libraries.

kotlin
[versions]
composeBom = "2024.02.01"
activityCompose = "1.8.2"

[libraries]
androidx-compose-bom = { group = "androidx.compose", name = "compose-bom", version.ref = "composeBom" }
androidx-ui = { group = "androidx.compose.ui", name = "ui" }
androidx-ui-graphics = { group = "androidx.compose.ui", name = "ui-graphics" }
androidx-ui-tooling-preview = { group = "androidx.compose.ui", name = "ui-tooling-preview" }
androidx-material3 = { group = "androidx.compose.material3", name = "material3" }
androidx-activity-compose = { group = "androidx.activity", name = "activity-compose", version.ref = "activityCompose" }

2. State Management Pattern (MVI/MVVM)

Use ViewModel with StateFlow to expose UI state. Avoid exposing MutableStateFlow.

kotlin
// UI State Definition
data class UserUiState(
    val isLoading: Boolean = false,
    val user: User? = null,
    val error: String? = null
)

// ViewModel
class UserViewModel @Inject constructor(
    private val userRepository: UserRepository
) : ViewModel() {

    private val _uiState = MutableStateFlow(UserUiState())
    val uiState: StateFlow<UserUiState> = _uiState.asStateFlow()

    fun loadUser() {
        viewModelScope.launch {
            _uiState.update { it.copy(isLoading = true) }
            try {
                val user = userRepository.getUser()
                _uiState.update { it.copy(user = user, isLoading = false) }
            } catch (e: Exception) {
                _uiState.update { it.copy(error = e.message, isLoading = false) }
            }
        }
    }
}

3. Creating the Screen Composable

Consume the state in a "Screen" composable and pass data down to stateless components.

kotlin
@Composable
fun UserScreen(
    viewModel: UserViewModel = hiltViewModel()
) {
    val uiState by viewModel.uiState.collectAsStateWithLifecycle()

    UserContent(
        uiState = uiState,
        onRetry = viewModel::loadUser
    )
}

@Composable
fun UserContent(
    uiState: UserUiState,
    onRetry: () -> Unit
) {
    Scaffold { padding ->
        Box(modifier = Modifier.padding(padding)) {
            when {
                uiState.isLoading -> CircularProgressIndicator()
                uiState.error != null -> ErrorView(uiState.error, onRetry)
                uiState.user != null -> UserProfile(uiState.user)
            }
        }
    }
}

Examples

Example 1: Type-Safe Navigation

Using the new Navigation Compose Type Safety (available in recent versions).

kotlin
// Define Destinations
@Serializable
object Home

@Serializable
data class Profile(val userId: String)

// Setup NavHost
@Composable
fun AppNavHost(navController: NavHostController) {
    NavHost(navController, startDestination = Home) {
        composable<Home> {
            HomeScreen(onNavigateToProfile = { id ->
                navController.navigate(Profile(userId = id))
            })
        }
        composable<Profile> { backStackEntry ->
            val profile: Profile = backStackEntry.toRoute()
            ProfileScreen(userId = profile.userId)
        }
    }
}

Best Practices

  • ✅ Do: Use remember and derivedStateOf to minimize unnecessary calculations during recomposition.
  • ✅ Do: Mark data classes used in UI state as @Immutable or @Stable if they contain List or other unstable types to enable smart recomposition skipping.
  • ✅ Do: Use LaunchedEffect for one-off side effects (like showing a Snackbar) triggered by state changes.
  • ❌ Don't: Perform expensive operations (like sorting a list) directly inside the Composable function body without remember.
  • ❌ Don't: Pass ViewModel instances down to child components. Pass only the data (state) and lambda callbacks (events).

Troubleshooting

Problem: Infinite Recomposition loop. Solution: Check if you are creating new object instances (like List or Modifier) inside the composition without remember, or if you are updating state inside the composition phase instead of a side-effect or callback. Use Layout Inspector to debug recomposition counts.

Frequently asked questions

What does the Android Jetpack Compose Expert AI skill do?

Expert guidance for building modern Android UIs with Jetpack Compose, covering state management, navigation, performance, and Material Design 3.

Why use Android Jetpack Compose Expert on TypingMind?

Because you install it once and use it with any model. Android Jetpack Compose Expert 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 Android Jetpack Compose Expert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kursku/skills/tree/master/packs/global-skillshare-import/wave-001/android-jetpack-compose-expert. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Android Jetpack Compose Expert?

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 Android Jetpack Compose Expert?

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

Is the Android Jetpack Compose Expert AI skill free?

It is published on GitHub by kursku. 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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