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springboot-verification

Verifizierungsschleife für Spring Boot Projekte: Build, statische Analyse, Tests mit Abdeckung, Sicherheitsscans und Diff-Review vor Release oder PR.

Was ist springboot-verification?

Diese Fähigkeit definiert eine vollständige Verifizierungsschleife für Spring Boot Projekte, die vor Pull-Requests, nach größeren Änderungen oder vor der Bereitstellung ausgeführt werden sollte. Sie umfasst sechs Phasen: Build, statische Analyse (SpotBugs, PMD, Checkstyle), Tests mit Codeabdeckung (JaCoCo) inklusive Unit-, Integrations- und API-Tests, einen Sicherheitsscan mit OWASP Dependency-Check und Secret-Suche, optionale Linting/Formatierung (Spotless) sowie einen abschließenden Diff-Review mit Checkliste. Die Skill wird für Maven und Gradle bereitgestellt und liefert einen standardisierten Prüfbericht. Der kontinuierliche Modus empfiehlt, die Phasen alle 30–60 Minuten zu wiederholen, um schnelles Feedback zu gewährleisten.

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

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Öffnet einen neuen Chat, in dem dieser Agent-Skill bereits geladen ist.

Dokumentation

Spring Boot Verifizierungsschleife

Vor PRs, nach größeren Änderungen und vor der Bereitstellung ausführen.

Wann aktivieren

  • Vor dem Öffnen eines Pull-Requests für einen Spring Boot Service
  • Nach größeren Refactorings oder Abhängigkeitsupgrades
  • Vor der Bereitstellungsverifizierung für Staging oder Produktion
  • Ausführung der vollständigen Build → Lint → Test → Sicherheitsscan-Pipeline
  • Validierung, dass die Testabdeckung Schwellenwerte erreicht

Phase 1: Build

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

Wenn der Build fehlschlägt, anhalten und reparieren.

Phase 2: Statische Analyse

Maven (gängige Plugins):

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

Gradle (falls konfiguriert):

./gradlew checkstyleMain pmdMain spotbugsMain

Phase 3: Tests + Abdeckung

mvn -T 4 test
mvn jacoco:report   # 80 %+ Abdeckung prüfen
# oder
./gradlew test jacocoTestReport

Bericht:

  • Gesamte Tests, bestanden/fehlgeschlagen
  • Abdeckung % (Zeilen/Zweige)

Unit-Tests

Service-Logik isoliert mit gemockten Abhängigkeiten testen:

@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);
  }
}

Integrationstests mit Testcontainers

Gegen eine echte Datenbank statt H2 testen:

@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");
  }
}

API-Tests mit MockMvc

Controller-Ebene mit vollem Spring-Kontext testen:

@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());
  }
}

Phase 4: Sicherheitsscan

# Abhängigkeits-CVEs
mvn org.owasp:dependency-check-maven:check
# oder
./gradlew dependencyCheckAnalyze

# Geheimnisse im Quellcode
grep -rn "password\s*=\s*\"" src/ --include="*.java" --include="*.yml" --include="*.properties"
grep -rn "sk-\|api_key\|secret" src/ --include="*.java" --include="*.yml"

# Geheimnisse (Git-Verlauf)
git secrets --scan  # falls konfiguriert

Häufige Sicherheitsbefunde

# Nach System.out.println suchen (Logger verwenden)
grep -rn "System\.out\.print" src/main/ --include="*.java"

# Nach rohen Ausnahmemeldungen in Antworten suchen
grep -rn "e\.getMessage()" src/main/ --include="*.java"

# Nach Wildcard-CORS suchen
grep -rn "allowedOrigins.*\*" src/main/ --include="*.java"

Phase 5: Lint/Format (optionales Tor)

mvn spotless:apply   # falls Spotless-Plugin verwendet wird
./gradlew spotlessApply

Phase 6: Diff-Review

git diff --stat
git diff

Checkliste:

  • Keine Debug-Logs hinterlassen (System.out, log.debug ohne Guards)
  • Aussagekräftige Fehler und HTTP-Statuscodes
  • Transaktionen und Validierungen vorhanden, wo nötig
  • Konfigurationsänderungen dokumentiert

Ausgabevorlage

VERIFIZIERUNGSBERICHT
=====================
Build:     [PASS/FAIL]
Statisch:  [PASS/FAIL] (spotbugs/pmd/checkstyle)
Tests:     [PASS/FAIL] (X/Y bestanden, Z% Abdeckung)
Sicherh.:  [PASS/FAIL] (CVE-Funde: N)
Diff:      [X Dateien geändert]

Gesamt:    [BEREIT / NICHT BEREIT]

Zu behebende Probleme:
1. ...
2. ...

Kontinuierlicher Modus

  • Phasen bei wesentlichen Änderungen oder alle 30–60 Minuten in langen Sitzungen erneut ausführen
  • Kurze Schleife beibehalten: mvn -T 4 test + spotbugs für schnelles Feedback

Denken Sie daran: Schnelles Feedback schlägt späte Überraschungen. Halten Sie das Tor streng – behandeln Sie Warnungen in Produktionssystemen als Fehler.

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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