quarkus-panache-smells
Detects and refactors ORM code smells in Quarkus Panache applications using the Repository pattern. Use when reviewing PanacheRepository code, diagnosing N+1 queries, data overfetching, or pagination issues.
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Detects and refactors ORM code smells in Quarkus Panache applications using the Repository pattern. Use when reviewing PanacheRepository code, diagnosing N+1 queries, data overfetching, or pagination issues.
REST integration testing patterns with JUnit 5, Mockito, RestAssured. Use when writing integration tests that mock external dependencies, use Testcontainers/H2 for databases, and test endpoints with raw JSON bo...
Constructor-based MapStruct mapping for compile-time safety in Jakarta EE. Use when implementing DTO mapping or using @Default annotations.
Detects violations of Clean Code principles and suggests refactorings. Use when reviewing code quality, improving readability, or refactoring methods, classes, and modules.
Detects opportunities to apply GoF Design Patterns in Jakarta EE/MicroProfile. Use when reviewing code for structural improvements or implementing creational, structural, or behavioral patterns.
Measures and limits cognitive load in Jakarta EE/MicroProfile code. Use when reviewing code complexity, designing services/entities, or identifying when to extract abstractions.
REST API design patterns and MicroProfile OpenAPI documentation. Use when designing endpoints, choosing HTTP methods, status codes, or documenting APIs with OpenAPI annotations.
Practical DDD patterns for Jakarta EE web applications with cognitive load distribution. Use when designing controllers, entities, services, or evaluating cohesion and load balance.
Identifies code smells and applies refactoring techniques from Martin Fowler's catalog. Use when improving code structure, reducing complexity, or eliminating smells without changing behavior.
Lombok annotations and best practices for Java 21+ projects. Use when reducing boilerplate, configuring builders, or choosing between Lombok and Records.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.