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kotlin-coroutines-flows

Kotlin Coroutines and Flow patterns for Android and KMP — structured concurrency, Flow operators, StateFlow, error handling, and testing. Use when writing coroutines or Flow code on Android or KMP, or debugging cancellation and concurrency.

¿Qué es kotlin-coroutines-flows?

kotlin-coroutines-flows is a Claude Code agent skill that kotlin Coroutines and Flow patterns for Android and KMP — structured concurrency, Flow operators, StateFlow, error handling, and testing. Use when writing coroutines or Flow code on Android or KMP, or debugging cancellation and concurrency.

Compatible con~Claude Code~Codex CLI~Cursor
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Documentación

Kotlin Coroutines & Flows

Patterns for structured concurrency, Flow-based reactive streams, and coroutine testing in Android and Kotlin Multiplatform projects.

When to Activate

  • Writing async code with Kotlin coroutines
  • Using Flow, StateFlow, or SharedFlow for reactive data
  • Handling concurrent operations (parallel loading, debounce, retry)
  • Testing coroutines and Flows
  • Managing coroutine scopes and cancellation

Structured Concurrency

Scope Hierarchy

Application
  └── viewModelScope (ViewModel)
        └── coroutineScope { } (structured child)
              ├── async { } (concurrent task)
              └── async { } (concurrent task)

Always use structured concurrency — never GlobalScope:

// BAD
GlobalScope.launch { fetchData() }

// GOOD — scoped to ViewModel lifecycle
viewModelScope.launch { fetchData() }

// GOOD — scoped to composable lifecycle
LaunchedEffect(key) { fetchData() }

Parallel Decomposition

Use coroutineScope + async for parallel work:

suspend fun loadDashboard(): Dashboard = coroutineScope {
    val items = async { itemRepository.getRecent() }
    val stats = async { statsRepository.getToday() }
    val profile = async { userRepository.getCurrent() }
    Dashboard(
        items = items.await(),
        stats = stats.await(),
        profile = profile.await()
    )
}

SupervisorScope

Use supervisorScope when child failures should not cancel siblings:

suspend fun syncAll() = supervisorScope {
    launch { syncItems() }       // failure here won't cancel syncStats
    launch { syncStats() }
    launch { syncSettings() }
}

Flow Patterns

Cold Flow — One-Shot to Stream Conversion

fun observeItems(): Flow<List<Item>> = flow {
    // Re-emits whenever the database changes
    itemDao.observeAll()
        .map { entities -> entities.map { it.toDomain() } }
        .collect { emit(it) }
}

StateFlow for UI State

class DashboardViewModel(
    observeProgress: ObserveUserProgressUseCase
) : ViewModel() {
    val progress: StateFlow<UserProgress> = observeProgress()
        .stateIn(
            scope = viewModelScope,
            started = SharingStarted.WhileSubscribed(5_000),
            initialValue = UserProgress.EMPTY
        )
}

WhileSubscribed(5_000) keeps the upstream active for 5 seconds after the last subscriber leaves — survives configuration changes without restarting.

Combining Multiple Flows

val uiState: StateFlow<HomeState> = combine(
    itemRepository.observeItems(),
    settingsRepository.observeTheme(),
    userRepository.observeProfile()
) { items, theme, profile ->
    HomeState(items = items, theme = theme, profile = profile)
}.stateIn(viewModelScope, SharingStarted.WhileSubscribed(5_000), HomeState())

Flow Operators

// Debounce search input
searchQuery
    .debounce(300)
    .distinctUntilChanged()
    .flatMapLatest { query -> repository.search(query) }
    .catch { emit(emptyList()) }
    .collect { results -> _state.update { it.copy(results = results) } }

// Retry with exponential backoff
fun fetchWithRetry(): Flow<Data> = flow { emit(api.fetch()) }
    .retryWhen { cause, attempt ->
        if (cause is IOException && attempt < 3) {
            delay(1000L * (1 shl attempt.toInt()))
            true
        } else {
            false
        }
    }

SharedFlow for One-Time Events

class ItemListViewModel : ViewModel() {
    private val _effects = MutableSharedFlow<Effect>()
    val effects: SharedFlow<Effect> = _effects.asSharedFlow()

    sealed interface Effect {
        data class ShowSnackbar(val message: String) : Effect
        data class NavigateTo(val route: String) : Effect
    }

    private fun deleteItem(id: String) {
        viewModelScope.launch {
            repository.delete(id)
            _effects.emit(Effect.ShowSnackbar("Item deleted"))
        }
    }
}

// Collect in Composable
LaunchedEffect(Unit) {
    viewModel.effects.collect { effect ->
        when (effect) {
            is Effect.ShowSnackbar -> snackbarHostState.showSnackbar(effect.message)
            is Effect.NavigateTo -> navController.navigate(effect.route)
        }
    }
}

Dispatchers

// CPU-intensive work
withContext(Dispatchers.Default) { parseJson(largePayload) }

// IO-bound work
withContext(Dispatchers.IO) { database.query() }

// Main thread (UI) — default in viewModelScope
withContext(Dispatchers.Main) { updateUi() }

In KMP, use Dispatchers.Default and Dispatchers.Main (available on all platforms). Dispatchers.IO is JVM/Android only — use Dispatchers.Default on other platforms or provide via DI.

Cancellation

Cooperative Cancellation

Long-running loops must check for cancellation:

suspend fun processItems(items: List<Item>) = coroutineScope {
    for (item in items) {
        ensureActive()  // throws CancellationException if cancelled
        process(item)
    }
}

Cleanup with try/finally

viewModelScope.launch {
    try {
        _state.update { it.copy(isLoading = true) }
        val data = repository.fetch()
        _state.update { it.copy(data = data) }
    } finally {
        _state.update { it.copy(isLoading = false) }  // always runs, even on cancellation
    }
}

Testing

Testing StateFlow with Turbine

@Test
fun `search updates item list`() = runTest {
    val fakeRepository = FakeItemRepository().apply { emit(testItems) }
    val viewModel = ItemListViewModel(GetItemsUseCase(fakeRepository))

    viewModel.state.test {
        assertEquals(ItemListState(), awaitItem())  // initial

        viewModel.onSearch("query")
        val loading = awaitItem()
        assertTrue(loading.isLoading)

        val loaded = awaitItem()
        assertFalse(loaded.isLoading)
        assertEquals(1, loaded.items.size)
    }
}

Testing with TestDispatcher

@Test
fun `parallel load completes correctly`() = runTest {
    val viewModel = DashboardViewModel(
        itemRepo = FakeItemRepo(),
        statsRepo = FakeStatsRepo()
    )

    viewModel.load()
    advanceUntilIdle()

    val state = viewModel.state.value
    assertNotNull(state.items)
    assertNotNull(state.stats)
}

Faking Flows

class FakeItemRepository : ItemRepository {
    private val _items = MutableStateFlow<List<Item>>(emptyList())

    override fun observeItems(): Flow<List<Item>> = _items

    fun emit(items: List<Item>) { _items.value = items }

    override suspend fun getItemsByCategory(category: String): Result<List<Item>> {
        return Result.success(_items.value.filter { it.category == category })
    }
}

Anti-Patterns to Avoid

  • Using GlobalScope — leaks coroutines, no structured cancellation
  • Collecting Flows in init {} without a scope — use viewModelScope.launch
  • Using MutableStateFlow with mutable collections — always use immutable copies: _state.update { it.copy(list = it.list + newItem) }
  • Catching CancellationException — let it propagate for proper cancellation
  • Using flowOn(Dispatchers.Main) to collect — collection dispatcher is the caller's dispatcher
  • Creating Flow in @Composable without remember — recreates the flow every recomposition

References

See skill: compose-multiplatform-patterns for UI consumption of Flows. See skill: android-clean-architecture for where coroutines fit in layers.

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/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.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

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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