/qe-test-generation
Generates durable-first tests — invariants, contracts, and property-based tests at boundaries that survive a reimplementation — plus unit, integration, and e2e coverage. Use when creating tests for new or changed code, filling coverage gaps, or migrating test suites between
$ npx -y skills add proffesor-for-testing/agentic-qe --skill qe-test-generation --agent claude-codeHow 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
/qe-test-generation
Context preview
The summary Claude sees to decide when to auto-load this skill.
Generates durable-first tests — invariants, contracts, and property-based tests at boundaries that survive a reimplementation — plus unit, integration, and e2e coverage. Use when creating tests for new or changed code, filling coverage gaps, or migrating test suites between
SKILL.md
qe-test-generation.SKILL.mdname: "qe-test-generation"
description: "Generates durable-first tests — invariants, contracts, and property-based tests at boundaries that survive a reimplementation — plus unit, integration, and e2e coverage. Use when creating tests for new or changed code, filling coverage gaps, or migrating test suites between Jest, Vitest, and Playwright."
trust_tier: 3
validation:
schema_path: schemas/output.json
validator_path: scripts/validate-config.json
eval_path: evals/qe-test-generation.yaml
QE Test Generation
Purpose
Guide the use of v3's AI-powered test generation capabilities including pattern-based test synthesis, multi-framework support, and intelligent test case derivation from code analysis.
Write durable-first (the core rule)
When AI makes code cheap to regenerate, the durable asset is the test that still holds after the implementation is thrown away and rewritten. Generate tests in **durability tiers**, and lead with the durable ones (ADR-113):
| Tier | What it is | Survives a rewrite? | When to write | |------|-----------|---------------------|---------------| | **Durable** | Invariants, contracts/schemas, property-based tests, behavioral e2e — specified at the module's public boundary | **Yes** | **Always — ≥1 per target** | | **Ephemeral** | Example-based unit tests, mock-call/interaction tests (TDD-London style) | No (coupled to impl) | For the red-green loop; label them, delete freely | | **Live** | Monitoring / drift / cost assertions that run against reality | Continuously | For deployed behavior |
**The language-swap heuristic:** *if reimplementing this module in another language would invalidate the test, the test is at the wrong boundary.* Push it up a tier — assert on the observable contract, not on how the current code happens to work.
Every generated target MUST include at least one **durable** assertion (an invariant, a contract check, or a property). Mock-call assertions (`toHaveBeenCalledWith`) are ephemeral by definition — never let them be the only thing testing a target. Tag each generated test `// @tier durable|ephemeral|live` so its lifetime is explicit.
These tests are graded as **oracles**: a good test passes against the real code and *fails* against a seeded bug (mutant). A test that asserts nothing, or only the happy path, kills no mutants and is rejected — see `/mutation-testing` and ADR-113.
Activation
- When generating tests for new code
- When improving test coverage
- When migrating tests between frameworks
- When applying TDD patterns
- When generating edge case tests
Quick Start
# Generate unit tests for a file
aqe test generate --file src/services/UserService.ts --framework jest
# Generate tests with coverage target
aqe test generate --scope src/api/ --coverage 90 --type unit
# Generate integration tests
aqe test generate --file src/controllers/AuthController.ts --type integration
# Generate from patterns
aqe test generate --pattern repository --target src/repositories/
Agent Workflow
// Spawn test generation agents — durable-first
Task("Generate durable-first tests", `
Analyze src/services/PaymentService.ts and generate Jest tests in tier order.
1. DURABLE (write these first, >=1 per public method):
- Invariants ("a refund never makes a balance negative")
- Contract/schema checks on inputs and outputs crossing the boundary
- Property-based tests (fast-check) over input ranges, not single examples
2. EPHEMERAL (the red-green loop; tag '// @tier ephemeral'):
- Specific happy-path examples and error paths
- Mock external dependencies ONLY — never let a mock-call assertion be the
only test for a method
Apply the language-swap check: if a Python rewrite of PaymentService would break
the test, move it up to the durable tier.
Output to tests/unit/services/PaymentService.test.ts
`, "qe-test-architect")
// Property + contract generation (first-class, not opt-in)
Task("Generate property and contract tests", `
For src/repositories/, derive:
- Properties: round-trip (write→read returns same), idempotence, ordering invariants
- Contracts: the repository interface schema, enforced on every CRUD result
These survive a storage-engine swap; example-based CRUD tests do not.
`, "qe-property-tester")Test Generation Strategies
1. Code Analysis Based
await testGenerator.analyzeAndGenerate({
source: 'src/services/OrderService.ts',
analysis: {
methods: true,
branches: true,
dependencies: true,
errorPaths: true
},
output: {
framework: 'jest',
style: 'describe-it',
assertions: 'expect'
}
});2. Pattern-Based Generation
await testGenerator.applyPattern({
pattern: 'service-layer',
targets: ['src/services/*.ts'],
customizations: {
mockStrategy: 'jest.mock',
asyncHandling: 'async-await',
errorAssertion: 'toThrow'
}
});3. Coverage-Driven Generation
await testGenerator.fillCoverageGaps({
coverageReport: 'coverage/lcov.info',
targetCoverage: 90,
prioritize: ['uncovered-branches', 'error-paths'],
maxTests: 50
});Framework Support
| Framework | Unit | Integration | E2E | Mocking | |-----------|------|-------------|-----|---------| | Jest | ✅ | ✅ | ⚠️ | jest.mock | | Vitest | ✅ | ✅ | ⚠️ | vi.mock | | Mocha | ✅ | ✅ | ❌ | sinon | | Pytest | ✅ | ✅ | ❌ | pytest-mock | | JUnit | ✅ | ✅ | ❌ | Mockito |
Test Quality Checks
quality_checks:
durability: # the primary check (ADR-113)
durable_assertions_per_target: 1 # >=1 invariant/contract/property each
language_swap_safe: true # would survive a reimplementation
tier_tags_present: true # every test tagged durable|ephemeral|live
fault_detection: # do the tests actually catch bugs?
mutation_score_min: 0.6 # kill rate against seeded mutants
no_assertionless_tests: trueRead more
name: "qe-test-generation" description: "Generates durable-first tests — invariants, contracts, and property-based tests at boundaries that survive a reimplementation — plus unit, integration, and e2e coverage. Use when creating tests for new or changed code, filling coverage gaps, or migrating test suites between Jest, Vitest, and Playwright." trust_tier: 3 validation: schema_path: schemas/output.json validator_path: scripts/validate-config.json eval_path: evals/qe-test-generation.yaml
QE Test Generation
Purpose
Guide the use of v3's AI-powered test generation capabilities including pattern-based test synthesis, multi-framework support, and intelligent test case derivation from code analysis.
Write durable-first (the core rule)
When AI makes code cheap to regenerate, the durable asset is the test that still holds after the implementation is thrown away and rewritten. Generate tests in **durability tiers**, and lead with the durable ones (ADR-113):
| Tier | What it is | Survives a rewrite? | When to write | |------|-----------|---------------------|---------------| | **Durable** | Invariants, contracts/schemas, property-based tests, behavioral e2e — specified at the module's public boundary | **Yes** | **Always — ≥1 per target** | | **Ephemeral** | Example-based unit tests, mock-call/interaction tests (TDD-London style) | No (coupled to impl) | For the red-green loop; label them, delete freely | | **Live** | Monitoring / drift / cost assertions that run against reality | Continuously | For deployed behavior |
**The language-swap heuristic:** *if reimplementing this module in another language would invalidate the test, the test is at the wrong boundary.* Push it up a tier — assert on the observable contract, not on how the current code happens to work.
Every generated target MUST include at least one **durable** assertion (an invariant, a contract check, or a property). Mock-call assertions (`toHaveBeenCalledWith`) are ephemeral by definition — never let them be the only thing testing a target. Tag each generated test `// @tier durable|ephemeral|live` so its lifetime is explicit.
These tests are graded as **oracles**: a good test passes against the real code and *fails* against a seeded bug (mutant). A test that asserts nothing, or only the happy path, kills no mutants and is rejected — see `/mutation-testing` and ADR-113.
Activation
- When generating tests for new code
- When improving test coverage
- When migrating tests between frameworks
- When applying TDD patterns
- When generating edge case tests
Quick Start
# Generate unit tests for a file aqe test generate --file src/services/UserService.ts --framework jest # Generate tests with coverage target aqe test generate --scope src/api/ --coverage 90 --type unit # Generate integration tests aqe test generate --file src/controllers/AuthController.ts --type integration # Generate from patterns aqe test generate --pattern repository --target src/repositories/
Agent Workflow
// Spawn test generation agents — durable-first
Task("Generate durable-first tests", `
Analyze src/services/PaymentService.ts and generate Jest tests in tier order.
1. DURABLE (write these first, >=1 per public method):
- Invariants ("a refund never makes a balance negative")
- Contract/schema checks on inputs and outputs crossing the boundary
- Property-based tests (fast-check) over input ranges, not single examples
2. EPHEMERAL (the red-green loop; tag '// @tier ephemeral'):
- Specific happy-path examples and error paths
- Mock external dependencies ONLY — never let a mock-call assertion be the
only test for a method
Apply the language-swap check: if a Python rewrite of PaymentService would break
the test, move it up to the durable tier.
Output to tests/unit/services/PaymentService.test.ts
`, "qe-test-architect")
// Property + contract generation (first-class, not opt-in)
Task("Generate property and contract tests", `
For src/repositories/, derive:
- Properties: round-trip (write→read returns same), idempotence, ordering invariants
- Contracts: the repository interface schema, enforced on every CRUD result
These survive a storage-engine swap; example-based CRUD tests do not.
`, "qe-property-tester")Test Generation Strategies
1. Code Analysis Based
await testGenerator.analyzeAndGenerate({
source: 'src/services/OrderService.ts',
analysis: {
methods: true,
branches: true,
dependencies: true,
errorPaths: true
},
output: {
framework: 'jest',
style: 'describe-it',
assertions: 'expect'
}
});2. Pattern-Based Generation
await testGenerator.applyPattern({
pattern: 'service-layer',
targets: ['src/services/*.ts'],
customizations: {
mockStrategy: 'jest.mock',
asyncHandling: 'async-await',
errorAssertion: 'toThrow'
}
});3. Coverage-Driven Generation
await testGenerator.fillCoverageGaps({
coverageReport: 'coverage/lcov.info',
targetCoverage: 90,
prioritize: ['uncovered-branches', 'error-paths'],
maxTests: 50
});Framework Support
| Framework | Unit | Integration | E2E | Mocking | |-----------|------|-------------|-----|---------| | Jest | ✅ | ✅ | ⚠️ | jest.mock | | Vitest | ✅ | ✅ | ⚠️ | vi.mock | | Mocha | ✅ | ✅ | ❌ | sinon | | Pytest | ✅ | ✅ | ❌ | pytest-mock | | JUnit | ✅ | ✅ | ❌ | Mockito |
Test Quality Checks
quality_checks:
durability: # the primary check (ADR-113)
durable_assertions_per_target: 1 # >=1 invariant/contract/property each
language_swap_safe: true # would survive a reimplementation
tier_tags_present: true # every test tagged durable|ephemeral|live
fault_detection: # do the tests actually catch bugs?
mutation_score_min: 0.6 # kill rate against seeded mutants
no_assertionless_tests: trueAI-powered quality engineering agents that generate tests, find coverage gaps, detect flaky tests, and learn your codebase patterns — across 11 coding agent platforms.
Repo: proffesor-for-testing/agentic-qe
Other skills on agentic-qe.
- /a11y-ally
Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
Open skill - /accessibility-testing
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
Open skill - /agentdb-advanced
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
Open skill - /agentdb-learning
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
Open skill - /agentdb-memory-patterns
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
Open skill - /agentdb-optimization
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
Open skill

