Create production-quality Android applications following Google's official architecture guidance and NowInAndroid best practices. Use when building Android apps with Kotlin, Jetpack Compose, MVVM architecture, Hilt dependency injection, Room database, or multi-module projects. Triggers on requests to create Android projects, screens, ViewModels, repositories, feature modules, or when asked about Android architecture patterns.
npx skills add https://github.com/dpconde/claude-android-skill --skill android-development
Build Android applications following Google's official architecture guidance, as demonstrated in the NowInAndroid reference app.
| Task | Reference File |
|------|----------------|
| Project structure & modules | modularization.md |
| Architecture layers (UI, Domain, Data) | architecture.md |
| Jetpack Compose patterns | compose-patterns.md |
| Gradle & build configuration | gradle-setup.md |
| Testing approach | testing.md |
Creating a new project?
→ Read modularization.md for project structure
→ Use templates in assets/templates/
Adding a new feature?
→ Create feature module with api and impl submodules
→ Follow patterns in architecture.md
Building UI screens?
→ Read compose-patterns.md
→ Create Screen + ViewModel + UiState
Setting up data layer?
→ Read data layer section in architecture.md
→ Create Repository + DataSource + DAO
┌─────────────────────────────────────────┐
│ UI Layer │
│ (Compose Screens + ViewModels) │
├─────────────────────────────────────────┤
│ Domain Layer │
│ (Use Cases - optional, for reuse) │
├─────────────────────────────────────────┤
│ Data Layer │
│ (Repositories + DataSources) │
└─────────────────────────────────────────┘
app/ # App module - navigation, scaffolding
feature/
├── featurename/
│ ├── api/ # Navigation keys (public)
│ └── impl/ # Screen, ViewModel, DI (internal)
core/
├── data/ # Repositories
├── database/ # Room DAOs, entities
├── network/ # Retrofit, API models
├── model/ # Domain models (pure Kotlin)
├── common/ # Shared utilities
├── ui/ # Reusable Compose components
├── designsystem/ # Theme, icons, base components
├── datastore/ # Preferences storage
└── testing/ # Test utilities
feature:myfeature:api module with navigation keyfeature:myfeature:impl module with:MyFeatureScreen.kt - Composable UIMyFeatureViewModel.kt - State holderMyFeatureUiState.kt - Sealed interface for statesMyFeatureNavigation.kt - Navigation setupMyFeatureModule.kt - Hilt DI module@HiltViewModel
class MyFeatureViewModel @Inject constructor(
private val myRepository: MyRepository,
) : ViewModel() {
val uiState: StateFlow<MyFeatureUiState> = myRepository
.getData()
.map { data -> MyFeatureUiState.Success(data) }
.stateIn(
scope = viewModelScope,
started = SharingStarted.WhileSubscribed(5_000),
initialValue = MyFeatureUiState.Loading,
)
fun onAction(action: MyFeatureAction) {
when (action) {
is MyFeatureAction.ItemClicked -> handleItemClick(action.id)
}
}
}
sealed interface MyFeatureUiState {
data object Loading : MyFeatureUiState
data class Success(val items: List<Item>) : MyFeatureUiState
data class Error(val message: String) : MyFeatureUiState
}
@Composable
internal fun MyFeatureRoute(
onNavigateToDetail: (String) -> Unit,
viewModel: MyFeatureViewModel = hiltViewModel(),
) {
val uiState by viewModel.uiState.collectAsStateWithLifecycle()
MyFeatureScreen(
uiState = uiState,
onAction = viewModel::onAction,
onNavigateToDetail = onNavigateToDetail,
)
}
@Composable
internal fun MyFeatureScreen(
uiState: MyFeatureUiState,
onAction: (MyFeatureAction) -> Unit,
onNavigateToDetail: (String) -> Unit,
) {
when (uiState) {
is MyFeatureUiState.Loading -> LoadingIndicator()
is MyFeatureUiState.Success -> ContentList(uiState.items, onAction)
is MyFeatureUiState.Error -> ErrorMessage(uiState.message)
}
}
interface MyRepository {
fun getData(): Flow<List<MyModel>>
suspend fun updateItem(id: String, data: MyModel)
}
internal class OfflineFirstMyRepository @Inject constructor(
private val localDataSource: MyDao,
private val networkDataSource: MyNetworkApi,
) : MyRepository {
override fun getData(): Flow<List<MyModel>> =
localDataSource.getAll().map { entities ->
entities.map { it.toModel() }
}
override suspend fun updateItem(id: String, data: MyModel) {
localDataSource.upsert(data.toEntity())
}
}
// Gradle version catalog (libs.versions.toml)
[versions]
kotlin = "1.9.x"
compose-bom = "2024.x.x"
hilt = "2.48"
room = "2.6.x"
coroutines = "1.7.x"
[libraries]
androidx-compose-bom = { group = "androidx.compose", name = "compose-bom", version.ref = "compose-bom" }
hilt-android = { group = "com.google.dagger", name = "hilt-android", version.ref = "hilt" }
room-runtime = { group = "androidx.room", name = "room-runtime", version.ref = "room" }
Use convention plugins in build-logic/ for consistent configuration:
AndroidApplicationConventionPlugin - App modulesAndroidLibraryConventionPlugin - Library modulesAndroidFeatureConventionPlugin - Feature modulesAndroidComposeConventionPlugin - Compose setupAndroidHiltConventionPlugin - Hilt setupSee gradle-setup.md for complete build configuration.
Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use biopython.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST searches, AlphaFold structures, enrichment analysis. Best for interactive exploration, simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript applications. Use when: bullmq, bull queue, redis queue, background job, job queue.
Create custom external web service APIs for Moodle LMS. Use when implementing web services for course management, user tracking, quiz operations, or custom plugin functionality. Covers parameter validation, database operations, error handling, service registration, and Moodle coding standards.
Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas/distances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.
Take dpconde/android-development from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.