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Test Data Management

  • 95 installs
  • 433 repo stars
  • Updated August 4, 2026
  • proffesor-for-testing/agentic-qe

test-data-management is a Claude Code skill for testing & qa.

About

test-data-management is a Claude Code skill for testing & qa. It helps solo builders move faster with AI-assisted development.

  • test-data-management
  • Testing & QA
  • AI-coding skill

Test Data Management by the numbers

  • 95 all-time installs (skills.sh)
  • +3 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #1,016 of 2,153 Testing & QA skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill test-data-management

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Listed on Skillselion
Installs95
repo stars433
Last updatedAugust 4, 2026
Repositoryproffesor-for-testing/agentic-qe

How do I helps with testing & qa tasks.?

Helps with testing & qa tasks.

Who is it for?

Best when you're working on testing & qa and need structured help with test data management.

Skip if: Teams with no testing & qa needs, or anyone wanting a generic chat assistant without this specific workflow.

When should I use this skill?

When you need to helps with testing & qa tasks., or when test-data-management is a claude code skill for testing & qa.

What you get

Structured output aligned to test-data-management: test-data-management, Testing & QA.

Files

SKILL.mdMarkdownGitHub ↗

Test Data Management

<default_to_action> When creating or managing test data: 1. NEVER use production PII directly 2. GENERATE synthetic data with faker libraries 3. ANONYMIZE production data if used (mask, hash) 4. ISOLATE test data (transactions, per-test cleanup) 5. SCALE with batch generation (10k+ records/sec)

Quick Data Strategy:

  • Unit tests: Minimal data (just enough)
  • Integration: Realistic data (full complexity)
  • Performance: Volume data (10k+ records)

Critical Success Factors:

  • 40% of test failures from inadequate data
  • GDPR fines up to €20M for PII violations
  • Never store production PII in test environments

</default_to_action>

Quick Reference Card

When to Use

  • Creating test datasets
  • Handling sensitive data
  • Performance testing with volume
  • GDPR/CCPA compliance

Data Strategies

TypeWhenSize
MinimalUnit tests1-10 records
RealisticIntegration100-1000 records
VolumePerformance10k+ records
Edge casesBoundary testingTargeted

---

Data Anonymization

// Masking
function maskEmail(email) {
  const [user, domain] = email.split('@');
  return `${user[0]}***@${domain}`;
}
// john@example.com → j***@example.com

function maskCreditCard(cc) {
  return `****-****-****-${cc.slice(-4)}`;
}
// 4242424242424242 → ****-****-****-4242

// Anonymize production data
const anonymizedUsers = prodUsers.map(user => ({
  id: user.id, // Keep ID for relationships
  email: `user-${user.id}@example.com`, // Fake email
  firstName: faker.person.firstName(), // Generated
  phone: null, // Remove PII
  createdAt: user.createdAt // Keep non-PII
}));

---

Database Transaction Isolation

// Best practice: use transactions for cleanup
beforeEach(async () => {
  await db.beginTransaction();
});

afterEach(async () => {
  await db.rollbackTransaction(); // Auto cleanup!
});

test('user registration', async () => {
  const user = await userService.register({
    email: 'test@example.com'
  });
  expect(user.id).toBeDefined();
  // Automatic rollback after test - no cleanup needed
});

---

Agent-Driven Data Generation

// High-speed generation with constraints
await Task("Generate Test Data", {
  schema: 'ecommerce',
  count: { users: 10000, products: 500, orders: 5000 },
  preserveReferentialIntegrity: true,
  constraints: {
    age: { min: 18, max: 90 },
    roles: ['customer', 'admin']
  }
}, "qe-test-data-architect");

// GDPR-compliant anonymization
await Task("Anonymize Production Data", {
  source: 'production-snapshot',
  piiFields: ['email', 'phone', 'ssn'],
  method: 'pseudonymization',
  retainStructure: true
}, "qe-test-data-architect");

---

Agent Coordination Hints

Memory Namespace

aqe/test-data-management/
├── schemas/*            - Data schemas
├── generators/*         - Generator configs
├── anonymization/*      - PII handling rules
└── fixtures/*           - Reusable fixtures

Fleet Coordination

const dataFleet = await FleetManager.coordinate({
  strategy: 'test-data-generation',
  agents: [
    'qe-test-data-architect',  // Generate data
    'qe-test-executor',        // Execute with data
    'qe-security-scanner'      // Validate no PII exposure
  ],
  topology: 'sequential'
});

---

Related Skills

  • database-testing - Schema and integrity testing
  • compliance-testing - GDPR/CCPA compliance
  • performance-testing - Volume data for perf tests

---

Remember

Never use production PII directly. Always use synthetic data or properly anonymized production snapshots.

With Agents: qe-test-data-architect generates 10k+ records/sec with realistic patterns, relationships, and constraints. Agents ensure GDPR/CCPA compliance automatically and eliminate test data bottlenecks.

Related skills

FAQ

What does test-data-management do?

test-data-management is a Claude Code skill for testing & qa.

When should I use test-data-management?

When you need to helps with testing & qa tasks., or when test-data-management is a claude code skill for testing & qa.

What are the main capabilities?

test-data-management; Testing & QA; AI-coding skill.

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