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quarkus-verification

Verification loop for Quarkus projects: build, static analysis, tests with coverage, security scans, native compilation, and diff review before release or PR.

quarkus-verification とは?

quarkus-verification is a Claude Code agent skill that verification loop for Quarkus projects: build, static analysis, tests with coverage, security scans, native compilation, and diff review before release or PR.

対応~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/quarkus-verification

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ドキュメント

Quarkus Verification Loop

Run before PRs, after major changes, and pre-deploy.

When to Activate

  • Before opening a pull request for a Quarkus service
  • After major refactoring or dependency upgrades
  • Pre-deployment verification for staging or production
  • Running full build → lint → test → security scan → native compilation pipeline
  • Validating test coverage meets thresholds (80%+)
  • Testing native image compatibility

Phase 1: Build

# Maven
mvn clean verify -DskipTests

# Gradle
./gradlew clean assemble -x test

If build fails, stop and fix compilation errors.

Phase 2: Static Analysis

Checkstyle, PMD, SpotBugs (Maven)

mvn checkstyle:check pmd:check spotbugs:check

SonarQube (if configured)

mvn sonar:sonar \
  -Dsonar.projectKey=my-quarkus-project \
  -Dsonar.host.url=http://localhost:9000 \
  -Dsonar.login=${SONAR_TOKEN}

Common Issues to Address

  • Unused imports or variables
  • Complex methods (high cyclomatic complexity)
  • Potential null pointer dereferences
  • Security issues flagged by SpotBugs

Phase 3: Tests + Coverage

# Run all tests
mvn clean test

# Generate coverage report
mvn jacoco:report

# Enforce coverage threshold (80%)
mvn jacoco:check

# Or with Gradle
./gradlew test jacocoTestReport jacocoTestCoverageVerification

Test Categories

Unit Tests

Test service logic with mocked dependencies:

@ExtendWith(MockitoExtension.class)
class UserServiceTest {
  @Mock UserRepository userRepository;
  @InjectMocks UserService userService;

  @Test
  void createUser_validInput_returnsUser() {
    var dto = new CreateUserDto("Alice", "[email protected]");

    // Panache persist() is void — use doNothing + verify
    doNothing().when(userRepository).persist(any(User.class));

    User result = userService.create(dto);

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

Integration Tests

Test with real database (Testcontainers):

@QuarkusTest
@QuarkusTestResource(PostgresTestResource.class)
class UserRepositoryIntegrationTest {

  @Inject
  UserRepository userRepository;

  @Test
  @Transactional
  void findByEmail_existingUser_returnsUser() {
    User user = new User();
    user.name = "Alice";
    user.email = "[email protected]";
    userRepository.persist(user);

    Optional<User> found = userRepository.findByEmail("[email protected]");

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

API Tests

Test REST endpoints with REST Assured:

@QuarkusTest
class UserResourceTest {

  @Test
  void createUser_validInput_returns201() {
    given()
        .contentType(ContentType.JSON)
        .body("""
            {"name": "Alice", "email": "[email protected]"}
            """)
        .when().post("/api/users")
        .then()
        .statusCode(201)
        .body("name", equalTo("Alice"));
  }

  @Test
  void createUser_invalidEmail_returns400() {
    given()
        .contentType(ContentType.JSON)
        .body("""
            {"name": "Alice", "email": "invalid"}
            """)
        .when().post("/api/users")
        .then()
        .statusCode(400);
  }
}

Coverage Report

Check target/site/jacoco/index.html for detailed coverage:

  • Overall line coverage (target: 80%+)
  • Branch coverage (target: 70%+)
  • Identify uncovered critical paths

Phase 4: Security Scanning

Dependency Vulnerabilities (Maven)

mvn org.owasp:dependency-check-maven:check

Review target/dependency-check-report.html for CVEs.

Quarkus Security Audit

# Check vulnerable extensions
mvn quarkus:audit

# List all extensions
mvn quarkus:list-extensions

OWASP ZAP (API Security Testing)

docker run -t ghcr.io/zaproxy/zaproxy:stable zap-api-scan.py \
  -t http://localhost:8080/q/openapi \
  -f openapi

Common Security Checks

  • All secrets in environment variables (not in code)
  • Input validation on all endpoints
  • Authentication/authorization configured
  • CORS properly configured
  • Security headers set
  • Passwords hashed with BCrypt
  • SQL injection protection (parameterized queries)
  • Rate limiting on public endpoints

Phase 5: Native Compilation

Test GraalVM native image compatibility:

# Build native executable
mvn package -Dnative

# Or with container
mvn package -Dnative -Dquarkus.native.container-build=true

# Test native executable
./target/*-runner

# Run basic smoke tests
curl http://localhost:8080/q/health/live
curl http://localhost:8080/q/health/ready

Native Image Troubleshooting

Common issues:

  • Reflection: Add reflection config for dynamic classes
  • Resources: Include resources with quarkus.native.resources.includes
  • JNI: Register JNI classes if using native libraries

Example reflection config:

@RegisterForReflection(targets = {MyDynamicClass.class})
public class ReflectionConfiguration {}

Phase 6: Performance Testing

Load Testing with K6

// load-test.js
import http from 'k6/http';
import { check } from 'k6';

export const options = {
  stages: [
    { duration: '30s', target: 50 },
    { duration: '1m', target: 100 },
    { duration: '30s', target: 0 },
  ],
};

export default function () {
  const res = http.get('http://localhost:8080/api/markets');
  check(res, {
    'status is 200': (r) => r.status === 200,
    'response time < 200ms': (r) => r.timings.duration < 200,
  });
}

Run:

k6 run load-test.js

Metrics to Monitor

  • Response time (p50, p95, p99)
  • Throughput (requests/sec)
  • Error rate
  • Memory usage
  • CPU usage

Phase 7: Health Checks

# Liveness
curl http://localhost:8080/q/health/live

# Readiness
curl http://localhost:8080/q/health/ready

# All health checks
curl http://localhost:8080/q/health

# Metrics (if enabled)
curl http://localhost:8080/q/metrics

Expected responses:

{
  "status": "UP",
  "checks": [
    {
      "name": "Database connection",
      "status": "UP"
    }
  ]
}

Phase 8: Container Image Build

# Build container image
mvn package -Dquarkus.container-image.build=true

# Or with specific registry
mvn package \
  -Dquarkus.container-image.build=true \
  -Dquarkus.container-image.registry=docker.io \
  -Dquarkus.container-image.group=myorg \
  -Dquarkus.container-image.tag=1.0.0

# Test container
docker run -p 8080:8080 myorg/my-quarkus-app:1.0.0

Container Security Scan

# Trivy
trivy image myorg/my-quarkus-app:1.0.0

# Grype
grype myorg/my-quarkus-app:1.0.0

Phase 9: Configuration Validation

# Check all configuration properties
mvn quarkus:info

# List all config sources
curl http://localhost:8080/q/dev/io.quarkus.quarkus-vertx-http/config

Environment-Specific Checks

  • Database URLs configured per environment
  • Secrets externalized (Vault, env vars)
  • Logging levels appropriate
  • CORS origins set correctly
  • Rate limiting configured
  • Monitoring/tracing enabled

Phase 10: Documentation Review

  • OpenAPI/Swagger docs up to date (/q/swagger-ui)
  • README has setup instructions
  • API changes documented
  • Migration guide for breaking changes
  • Configuration properties documented

Generate OpenAPI spec:

curl http://localhost:8080/q/openapi -o openapi.json

Verification Checklist

Code Quality

  • Build passes without warnings
  • Static analysis clean (no high/medium issues)
  • Code follows team conventions
  • No commented-out code or TODOs in PR

Testing

  • All tests pass
  • Code coverage ≥ 80%
  • Integration tests with real database
  • Security tests pass
  • Performance within acceptable limits

Security

  • No dependency vulnerabilities
  • Authentication/authorization tested
  • Input validation complete
  • Secrets not in source code
  • Security headers configured

Deployment

  • Native compilation successful
  • Container image builds
  • Health checks respond correctly
  • Configuration valid for target environment

Native Image

  • Native executable builds
  • Native tests pass
  • Startup time < 100ms
  • Memory footprint acceptable

Automated Verification Script

#!/bin/bash
set -e

echo "=== Phase 1: Build ==="
mvn clean verify -DskipTests

echo "=== Phase 2: Static Analysis ==="
mvn checkstyle:check pmd:check spotbugs:check

echo "=== Phase 3: Tests + Coverage ==="
mvn test jacoco:report jacoco:check

echo "=== Phase 4: Security Scan ==="
mvn org.owasp:dependency-check-maven:check

echo "=== Phase 5: Native Compilation ==="
mvn package -Dnative -Dquarkus.native.container-build=true

echo "=== All Phases Complete ==="
echo "Review reports:"
echo "  - Coverage: target/site/jacoco/index.html"
echo "  - Security: target/dependency-check-report.html"
echo "  - Native: target/*-runner"

CI/CD Integration

GitHub Actions Example

name: Verification

on: [push, pull_request]

jobs:
  verify:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v7

      - name: Set up JDK 21
        uses: actions/setup-java@v5
        with:
          java-version: '21'
          distribution: 'temurin'

      - name: Cache Maven packages
        uses: actions/cache@v6
        with:
          path: ~/.m2
          key: ${{ runner.os }}-m2-${{ hashFiles('**/pom.xml') }}

      - name: Build
        run: mvn clean verify -DskipTests

      - name: Test with Coverage
        run: mvn test jacoco:report jacoco:check

      - name: Security Scan
        run: mvn org.owasp:dependency-check-maven:check

      - name: Upload Coverage
        uses: codecov/codecov-action@v7
        with:
          token: ${{ secrets.CODECOV_TOKEN }}
          files: target/site/jacoco/jacoco.xml

Best Practices

  • Run verification loop before every PR
  • Automate in CI/CD pipeline
  • Fix issues immediately; don't accumulate debt
  • Keep coverage above 80%
  • Update dependencies regularly
  • Test native compilation periodically
  • Monitor performance trends
  • Document breaking changes
  • Review security scan results
  • Validate configuration for each environment

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/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

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.

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