Results for “gradle-kotlin-dsl”

Configure Kotlin build and quality tooling, including Gradle Kotlin DSL, Version Catalogs, KMP, ktlint, Detekt, MockK, coverage, and quality plugins. Use for Kotlin-specific build, lint, test-tool, or coverage setup; defer Java-only tooling and Spring test behavior.

Scaffolds a Spring Boot Kotlin project with Gradle, WebFlux, R2DBC, Redis, MongoDB, and Testcontainers, including Docker Compose setup.

地道的 Kotlin 模式、最佳实践和约定，用于用协程、空安全和 DSL 构建器构建健壮、高效、可维护的 Kotlin 应用。

Enforce idiomatic Kotlin conventions for null safety, immutability, sealed classes, coroutines, extension functions, DSL builders, and Gradle Kotlin DSL.

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders.

Provides idiomatic Kotlin implementation patterns including coroutine concurrency, Flow stream handling, multiplatform architecture, Compose UI construction, Ktor server setup, and type-safe DSL design.

Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders.

Incrementally fixes Gradle build and compilation errors for Android and Kotlin Multiplatform projects.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.

Provides best practices for building idiomatic Spring Boot applications with Kotlin, covering project setup, dependency injection, configuration, web layer, services, data layer, testing, and coroutines.

Write reliable Kotlin tests using Kotest, MockK, coroutine testing, property-based testing, and Kover coverage, following a TDD workflow.

Guides Android native app development with Material Design 3, Kotlin/Compose, project configuration, accessibility, and build troubleshooting.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.

Write reliable, maintainable Kotlin tests using Kotest, MockK, coroutine testing, property-based testing, and Kover coverage following TDD methodology.

Provides Ktor server patterns including routing DSL, plugins, authentication, Koin DI, kotlinx.serialization, WebSockets, and testApplication testing.

Configure Maven, Gradle, and static analysis for Java projects. Use for Java-only build and quality tooling such as Spotless, Checkstyle, SpotBugs, SonarLint, JDK versions, and Java service Dockerfiles; defer Kotlin, Android, Flutter, and GitHub Actions-specific configuration.

Write idiomatic Kotlin 1.9+ with null safety, sealed classes, data classes, extension functions, delegates, collections, inline/reified generics, and expression syntax. Use for Kotlin language constructs, Java-to-Kotlin migration, lazy delegates, data classes, backing properties, or inline/reified generics; keep language constructs in scope even inside response models, and defer coroutine configuration, Android Context/framework, Retrofit/OkHttp client setup, and other library-specific recipes.

Kotlin testing patterns with Kotest, MockK, coroutine testing, property-based testing, and Kover coverage. Follows TDD methodology with idiomatic Kotlin practices.

Kotlin 测试模式，含 Kotest、MockK、协程测试、属性测试和 Kover 覆盖率。遵循 TDD 方法论，使用地道 Kotlin 实践。

Foundational Kotlin patterns covering null safety, coroutines, data classes, extension functions, and Kotlin idioms. Use when writing Kotlin code or needing guidance on Kotlin development. This is the entry point for Kotlin development.

Write high-performance GPU kernels using cuTile's tile-based programming model with validation and optimization, including deep agent orchestration for complex multi-kernel tasks.

Koin dependency injection framework for Kotlin. Use for Kotlin DI, Android development, Ktor backend, Compose Multiplatform, dependency injection patterns, and module definitions.

Persists app data on Android using Room, SQLite, SharedPreferences, DataStore, and encryption.

Guides setting up Drizzle ORM with Vercel Postgres and Vercel KV for a manufacturing analysis app, covering schema definition, queries, migrations, caching, sessions, and rate limiting.

Develops native Android apps with Kotlin and Java, covering UI, performance, and Play Store deployment.

Use when designing a Digital Down Converter (DDC) using dsphdl System objects. Triggers on requests involving DDC design, frequency down-conversion for FPGA/ASIC, NCO + mixer + decimation filter chains, fractional/non-integer sample rate conversion, or HDL-optimized receiver front-end signal processing.

Kotest — flexible, idiomatic Kotlin testing framework. Multiple specification styles (StringSpec, FunSpec, BehaviorSpec, DescribeSpec, FeatureSpec, FreeSpec), rich matcher library, property-based testing, data-driven tests, coroutine support, KMP-friendly. Drop-in alternative or complement to JUnit. USE WHEN: user mentions "Kotest", "io.kotest", "shouldBe", "StringSpec", "BehaviorSpec", "DescribeSpec", "kotest property testing", "Arb.list", "forAll", "kotest matchers", "kotlin tests" DO NOT USE FOR: JUnit-specific patterns - use junit skill (or framework-specific test skills) DO NOT USE FOR: Flow testing - use `testing/turbine` DO NOT USE FOR: Compose snapshot tests - use `testing/compose-snapshot` DO NOT USE FOR: Mobile E2E - use `testing/maestro`

We need to output a SKILL.md file with the specified format.

Integrates Flutter apps with native iOS (Swift/UIKit) and Android (Kotlin/Android SDK) APIs, covering native UI components, camera access, file system, and app extensions.

Guides production-grade Android and cross-platform app development covering stack selection, architecture, UI, testing, build, and release.

Enable MIPI/GMSL camera sensors on a Jetson Thor or Orin custom carrier by rendering a kernel-DT overlay from the in-tree sensor DTSI.

Toggle the statusline quota pace indicator (mode/theme)

Designs and implements a Kotlin algorithm that predicts the next app page and its resources using page access counts and graph-based reachability, without machine learning.

Imported skill redlining from anthropic