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springboot-verification

Bucle de verificación para proyectos Spring Boot: compilación, análisis estático, pruebas con cobertura, escaneos de seguridad y revisión de diferencias antes de un PR o lanzamiento.

¿Qué es springboot-verification?

Esta habilidad define un pipeline de verificación completo para proyectos Spring Boot, diseñado para ejecutarse antes de abrir Pull Requests, después de cambios importantes y previo al despliegue. Abarca seis fases: compilación (Maven/Gradle), análisis estático con SpotBugs, PMD y Checkstyle, pruebas unitarias y de integración con cobertura mínima del 80%, escaneo de seguridad de dependencias y secretos, linting opcional y revisión de diferencias. Incluye ejemplos concretos de código Java para pruebas con Mockito, Testcontainers (PostgreSQL real) y MockMvc para APIs REST. Al final produce un informe resumido con estado de cada fase. La habilidad es útil para mantener la calidad del código, detectar vulnerabilidades temprano y asegurar que el software esté listo para producción, funcionando en proyectos que usan Maven o Gradle.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/springboot-verification

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Documentación

Bucle de Verificación Spring Boot

Ejecutar antes de PRs, después de cambios importantes y previo al despliegue.

Cuándo Activarlo

  • Antes de abrir un pull request para un servicio Spring Boot
  • Después de una refactorización importante o actualización de dependencias
  • Verificación previa al despliegue en staging o producción
  • Ejecutar el pipeline completo: compilación → lint → pruebas → escaneo de seguridad
  • Validar que la cobertura de pruebas cumpla con los umbrales

Fase 1: Compilación

mvn -T 4 clean verify -DskipTests
# o
./gradlew clean assemble -x test

Si la compilación falla, detener y corregir.

Fase 2: Análisis Estático

Maven (plugins comunes):

mvn -T 4 spotbugs:check pmd:check checkstyle:check

Gradle (si está configurado):

./gradlew checkstyleMain pmdMain spotbugsMain

Fase 3: Pruebas + Cobertura

mvn -T 4 test
mvn jacoco:report   # verificar cobertura >= 80%
# o
./gradlew test jacocoTestReport

Informe:

  • Total de pruebas, pasadas/fallidas
  • % de cobertura (líneas/ramas)

Pruebas Unitarias

Probar la lógica del servicio de forma aislada con dependencias simuladas:

@ExtendWith(MockitoExtension.class)
class UserServiceTest {

  @Mock private UserRepository userRepository;
  @InjectMocks private UserService userService;

  @Test
  void createUser_validInput_returnsUser() {
    var dto = new CreateUserDto("Alice", "[email protected]");
    var expected = new User(1L, "Alice", "[email protected]");
    when(userRepository.save(any(User.class))).thenReturn(expected);

    var result = userService.create(dto);

    assertThat(result.name()).isEqualTo("Alice");
    verify(userRepository).save(any(User.class));
  }

  @Test
  void createUser_duplicateEmail_throwsException() {
    var dto = new CreateUserDto("Alice", "[email protected]");
    when(userRepository.existsByEmail(dto.email())).thenReturn(true);

    assertThatThrownBy(() -> userService.create(dto))
        .isInstanceOf(DuplicateEmailException.class);
  }
}

Pruebas de Integración con Testcontainers

Probar contra una base de datos real en lugar de H2:

@SpringBootTest
@Testcontainers
class UserRepositoryIntegrationTest {

  @Container
  static PostgreSQLContainer<?> postgres = new PostgreSQLContainer<>("postgres:16-alpine")
      .withDatabaseName("testdb");

  @DynamicPropertySource
  static void configureProperties(DynamicPropertyRegistry registry) {
    registry.add("spring.datasource.url", postgres::getJdbcUrl);
    registry.add("spring.datasource.username", postgres::getUsername);
    registry.add("spring.datasource.password", postgres::getPassword);
  }

  @Autowired private UserRepository userRepository;

  @Test
  void findByEmail_existingUser_returnsUser() {
    userRepository.save(new User("Alice", "[email protected]"));

    var found = userRepository.findByEmail("[email protected]");

    assertThat(found).isPresent();
    assertThat(found.get().getName()).isEqualTo("Alice");
  }
}

Pruebas de API con MockMvc

Probar la capa de controladores con el contexto completo de Spring:

@WebMvcTest(UserController.class)
class UserControllerTest {

  @Autowired private MockMvc mockMvc;
  @MockBean private UserService userService;

  @Test
  void createUser_validInput_returns201() throws Exception {
    var user = new UserDto(1L, "Alice", "[email protected]");
    when(userService.create(any())).thenReturn(user);

    mockMvc.perform(post("/api/users")
            .contentType(MediaType.APPLICATION_JSON)
            .content("""
                {"name": "Alice", "email": "[email protected]"}
                """))
        .andExpect(status().isCreated())
        .andExpect(jsonPath("$.name").value("Alice"));
  }

  @Test
  void createUser_invalidEmail_returns400() throws Exception {
    mockMvc.perform(post("/api/users")
            .contentType(MediaType.APPLICATION_JSON)
            .content("""
                {"name": "Alice", "email": "not-an-email"}
                """))
        .andExpect(status().isBadRequest());
  }
}

Fase 4: Escaneo de Seguridad

# CVEs de dependencias
mvn org.owasp:dependency-check-maven:check
# o
./gradlew dependencyCheckAnalyze

# Secretos en el código fuente
grep -rn "password\s*=\s*\"" src/ --include="*.java" --include="*.yml" --include="*.properties"
grep -rn "sk-\|api_key\|secret" src/ --include="*.java" --include="*.yml"

# Secretos (historial de git)
git secrets --scan  # si está configurado

Hallazgos Comunes de Seguridad

# Buscar System.out.println (usar logger en su lugar)
grep -rn "System\.out\.print" src/main/ --include="*.java"

# Buscar mensajes de excepción crudos en respuestas
grep -rn "e\.getMessage()" src/main/ --include="*.java"

# Buscar CORS con comodín
grep -rn "allowedOrigins.*\*" src/main/ --include="*.java"

Fase 5: Linting/Formato (puerta opcional)

mvn spotless:apply   # si se usa el plugin Spotless
./gradlew spotlessApply

Fase 6: Revisión de Diferencias

git diff --stat
git diff

Lista de verificación:

  • Sin registros de depuración (System.out, log.debug sin guardas)
  • Errores y estados HTTP significativos
  • Transacciones y validación presentes donde sea necesario
  • Cambios de configuración documentados

Plantilla de Salida

INFORME DE VERIFICACIÓN
=======================
Compilación:  [PASS/FAIL]
Estático:     [PASS/FAIL] (spotbugs/pmd/checkstyle)
Pruebas:      [PASS/FAIL] (X/Y pasadas, Z% cobertura)
Seguridad:    [PASS/FAIL] (Hallazgos CVE: N)
Diff:         [X archivos cambiados]

General:      [LISTO / NO LISTO]

Problemas a corregir:
1. ...
2. ...

Modo Continuo

  • Re-ejecutar fases en cambios significativos o cada 30–60 minutos en sesiones largas
  • Mantener un bucle corto: mvn -T 4 test + spotbugs para retroalimentación rápida

Recuerda: La retroalimentación rápida evita sorpresas tardías. Mantén la puerta estricta: trata las advertencias como defectos en sistemas de producción.

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.

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.

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