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android-clean-architecture

Android 和 Kotlin Multiplatform 项目的干净架构模式——模块结构、依赖规则、UseCase、Repository 及数据层模式。在组织模块、层次或数据流时使用。

android-clean-architecture 是什么?

该技能为 Android 和 Kotlin Multiplatform (KMP) 项目提供了一套完整的 Clean Architecture(干净架构)实现指南。明确定义了模块结构、依赖规则、领域层(UseCase、Repository 接口)、数据层(Room、SQLDelight、Ktor 集成)以及依赖注入(Koin/Hilt)的最佳实践。核心原则是 domain 层必须是纯 Kotlin,绝不依赖 data、presentation 或任何框架。技能还涵盖了错误处理(Result/Try 模式)、数据映射器、Gradle 约定插件以及常见反模式(如将业务逻辑放在 ViewModel 中、暴露数据库实体到 UI 层)。适用于 Android 原生和 KMP 跨平台项目,帮助开发者构建可测试、可维护、松耦合的应用程序。

兼容平台~Claude Code~Codex CLI~Cursor
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文档

Android Clean Architecture

适用于 Android 和 KMP 项目的 Clean Architecture 模式。涵盖模块边界、依赖倒置、UseCase/Repository 模式以及基于 Room、SQLDelight 和 Ktor 的数据层设计。

何时激活

  • 构建 Android 或 KMP 项目模块
  • 实现 UseCase、Repository 或 DataSource
  • 设计层间数据流(领域层、数据层、表现层)
  • 使用 Koin 或 Hilt 设置依赖注入
  • 在分层架构中使用 Room、SQLDelight 或 Ktor

模块结构

推荐布局

project/
├── app/                  # Android 入口点、DI 连接、Application 类
├── core/                 # 共享工具类、基类、错误类型
├── domain/               # UseCase、领域模型、仓库接口(纯 Kotlin)
├── data/                 # Repository 实现、DataSource、数据库、网络
├── presentation/         # 界面、ViewModel、UI 模型、导航
├── design-system/        # 可复用的 Compose 组件、主题、排版
└── feature/              # 功能模块(可选,用于大型项目)
    ├── auth/
    ├── settings/
    └── profile/

依赖规则

app → presentation, domain, data, core
presentation → domain, design-system, core
data → domain, core
domain → core(或不依赖任何模块)
core →(不依赖任何模块)

关键:domain 绝不能依赖 data、presentation 或任何框架。它只包含纯 Kotlin 代码。

领域层

UseCase 模式

每个 UseCase 代表一个业务操作。使用 operator fun invoke 实现清晰的调用点:

class GetItemsByCategoryUseCase(
    private val repository: ItemRepository
) {
    suspend operator fun invoke(category: String): Result<List<Item>> {
        return repository.getItemsByCategory(category)
    }
}

// 基于 Flow 的 UseCase,用于响应式数据流
class ObserveUserProgressUseCase(
    private val repository: UserRepository
) {
    operator fun invoke(userId: String): Flow<UserProgress> {
        return repository.observeProgress(userId)
    }
}

领域模型

领域模型是纯 Kotlin 数据类——没有框架注解:

data class Item(
    val id: String,
    val title: String,
    val description: String,
    val tags: List<String>,
    val status: Status,
    val category: String
)

enum class Status { DRAFT, ACTIVE, ARCHIVED }

Repository 接口

在领域层定义,在数据层实现:

interface ItemRepository {
    suspend fun getItemsByCategory(category: String): Result<List<Item>>
    suspend fun saveItem(item: Item): Result<Unit>
    fun observeItems(): Flow<List<Item>>
}

数据层

Repository 实现

协调本地和远程数据源:

class ItemRepositoryImpl(
    private val localDataSource: ItemLocalDataSource,
    private val remoteDataSource: ItemRemoteDataSource
) : ItemRepository {

    override suspend fun getItemsByCategory(category: String): Result<List<Item>> {
        return runCatching {
            val remote = remoteDataSource.fetchItems(category)
            localDataSource.insertItems(remote.map { it.toEntity() })
            localDataSource.getItemsByCategory(category).map { it.toDomain() }
        }
    }

    override suspend fun saveItem(item: Item): Result<Unit> {
        return runCatching {
            localDataSource.insertItems(listOf(item.toEntity()))
        }
    }

    override fun observeItems(): Flow<List<Item>> {
        return localDataSource.observeAll().map { entities ->
            entities.map { it.toDomain() }
        }
    }
}

Mapper 模式

将 Mapper 作为数据模型附近的扩展函数:

// 在数据层
fun ItemEntity.toDomain() = Item(
    id = id,
    title = title,
    description = description,
    tags = tags.split("|"),
    status = Status.valueOf(status),
    category = category
)

fun ItemDto.toEntity() = ItemEntity(
    id = id,
    title = title,
    description = description,
    tags = tags.joinToString("|"),
    status = status,
    category = category
)

Room 数据库(Android)

@Entity(tableName = "items")
data class ItemEntity(
    @PrimaryKey val id: String,
    val title: String,
    val description: String,
    val tags: String,
    val status: String,
    val category: String
)

@Dao
interface ItemDao {
    @Query("SELECT * FROM items WHERE category = :category")
    suspend fun getByCategory(category: String): List<ItemEntity>

    @Upsert
    suspend fun upsert(items: List<ItemEntity>)

    @Query("SELECT * FROM items")
    fun observeAll(): Flow<List<ItemEntity>>
}

SQLDelight(KMP)

-- Item.sq
CREATE TABLE ItemEntity (
    id TEXT NOT NULL PRIMARY KEY,
    title TEXT NOT NULL,
    description TEXT NOT NULL,
    tags TEXT NOT NULL,
    status TEXT NOT NULL,
    category TEXT NOT NULL
);

getByCategory:
SELECT * FROM ItemEntity WHERE category = ?;

upsert:
INSERT OR REPLACE INTO ItemEntity (id, title, description, tags, status, category)
VALUES (?, ?, ?, ?, ?, ?);

observeAll:
SELECT * FROM ItemEntity;

Ktor 网络客户端(KMP)

class ItemRemoteDataSource(private val client: HttpClient) {

    suspend fun fetchItems(category: String): List<ItemDto> {
        return client.get("api/items") {
            parameter("category", category)
        }.body()
    }
}

// 设置 HttpClient 及内容协商
val httpClient = HttpClient {
    install(ContentNegotiation) { json(Json { ignoreUnknownKeys = true }) }
    install(Logging) { level = LogLevel.HEADERS }
    defaultRequest { url("https://api.example.com/") }
}

依赖注入

Koin(兼容 KMP)

// Domain 模块
val domainModule = module {
    factory { GetItemsByCategoryUseCase(get()) }
    factory { ObserveUserProgressUseCase(get()) }
}

// Data 模块
val dataModule = module {
    single<ItemRepository> { ItemRepositoryImpl(get(), get()) }
    single { ItemLocalDataSource(get()) }
    single { ItemRemoteDataSource(get()) }
}

// Presentation 模块
val presentationModule = module {
    viewModelOf(::ItemListViewModel)
    viewModelOf(::DashboardViewModel)
}

Hilt(仅 Android)

@Module
@InstallIn(SingletonComponent::class)
abstract class RepositoryModule {
    @Binds
    abstract fun bindItemRepository(impl: ItemRepositoryImpl): ItemRepository
}

@HiltViewModel
class ItemListViewModel @Inject constructor(
    private val getItems: GetItemsByCategoryUseCase
) : ViewModel()

错误处理

Result/Try 模式

使用 Result<T> 或自定义密封类型进行错误传播:

sealed interface Try<out T> {
    data class Success<T>(val value: T) : Try<T>
    data class Failure(val error: AppError) : Try<Nothing>
}

sealed interface AppError {
    data class Network(val message: String) : AppError
    data class Database(val message: String) : AppError
    data object Unauthorized : AppError
}

// 在 ViewModel 中——映射到 UI 状态
viewModelScope.launch {
    when (val result = getItems(category)) {
        is Try.Success -> _state.update { it.copy(items = result.value, isLoading = false) }
        is Try.Failure -> _state.update { it.copy(error = result.error.toMessage(), isLoading = false) }
    }
}

约定插件(Gradle)

对于 KMP 项目,使用约定插件减少构建文件重复:

// build-logic/src/main/kotlin/kmp-library.gradle.kts
plugins {
    id("org.jetbrains.kotlin.multiplatform")
}

kotlin {
    androidTarget()
    iosX64(); iosArm64(); iosSimulatorArm64()
    sourceSets {
        commonMain.dependencies { /* 共享依赖 */ }
        commonTest.dependencies { implementation(kotlin("test")) }
    }
}

在模块中应用:

// domain/build.gradle.kts
plugins { id("kmp-library") }

应避免的反模式

  • 在 domain 层中导入 Android 框架类——保持纯 Kotlin
  • 将数据库实体或 DTO 暴露给 UI 层——始终映射为领域模型
  • 将业务逻辑放在 ViewModel 中——提取到 UseCase
  • 使用 GlobalScope 或无结构协程——使用 viewModelScope 或结构化并发
  • 臃肿的 Repository 实现——拆分为专注的 DataSource
  • 循环模块依赖——如果 A 依赖 B,则 B 不能依赖 A

参考

UI 模式请参见技能:compose-multiplatform-patterns 异步模式请参见技能:kotlin-coroutines-flows

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

api-connector-builder

Build a new API connector or provider by matching the target repo

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