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/test-data-management

Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios.

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agentic-qe
436200 skills169 agents149 commands
Install
$ npx -y skills add proffesor-for-testing/agentic-qe --skill test-data-management --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/test-data-management

Context preview

The summary Claude sees to decide when to auto-load this skill.

Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios.

SKILL.md

test-data-management.SKILL.md
name: test-data-management
description: "Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios."
category: specialized-testing
priority: high
tokenEstimate: 1000
agents: [qe-test-data-architect, qe-test-executor, qe-security-scanner]
implementation_status: optimized
optimization_version: 1.0
last_optimized: 2025-12-02
dependencies: []
quick_reference_card: true
tags: [test-data, faker, synthetic, gdpr, pii, anonymization, factories]
trust_tier: 3
validation:
  schema_path: schemas/output.json
  validator_path: scripts/validate-config.json
  eval_path: evals/test-data-management.yaml

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

| Type | When | Size | |------|------|------| | **Minimal** | Unit tests | 1-10 records | | **Realistic** | Integration | 100-1000 records | | **Volume** | Performance | 10k+ records | | **Edge cases** | Boundary testing | Targeted |

---

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](../database-testing/) - Schema and integrity testing
  • [compliance-testing](../compliance-testing/) - GDPR/CCPA compliance
  • [performance-testing](../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.

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