Harness Checklist

Published 2026-04-18·Updated 2026-10-29·5 min read

AI documentation guide

Required and optional harnesses organized by pattern.

Required Harnesses by Pattern

Table 1. Required and optional harnesses with priority by MSA pattern

Pattern	Required Harnesses	Optional Harnesses	Priority
L1: CRUD	- API contract verification - Basic unit tests - Integration tests	- Performance tests - Security scans	P0
L2: Sync MSA	- Service contract verification - Timeout/retry - Circuit breaker - Contract Testing	- Chaos engineering - Load tests	P1
L3: Async Events	- Event schema verification - Idempotency harness - Event ordering verification - Eventually Consistent tests	- Event replay - Dead Letter Queue	P1
L4: Saga	- Saga step verification - Compensating transaction verification - Failure scenario tests - Timeout harness	- Distributed tracing - Chaos engineering	P0
L5: Event Sourcing	- Event schema verification - Projection verification - Event replay - Event migration	- Snapshot strategy - Performance tests	P0

Harness Implementation Examples

Idempotency Harness (L3+)

# harness/idempotency_test.py
def test_duplicate_event_handling():
    """Verify identical results when receiving same event multiple times"""
    event = OrderCreatedEvent(orderId="123", userId="U1", items=[])

    # First processing
    result1 = event_handler.handle(event)
    state1 = get_order_state("123")

    # Second processing (duplicate)
    result2 = event_handler.handle(event)
    state2 = get_order_state("123")

    # Results must be identical
    assert result1 == result2
    assert state1 == state2

Compensating Transaction Harness (L4+)

# harness/saga_compensation_test.py
def test_saga_compensation():
    """Verify that compensation logic works correctly on Saga failure"""
    saga = TravelBookingSaga()

    # 1. Flight reservation success
    saga.execute_step("ReserveFlight")
    assert flight_service.is_reserved("flight123")

    # 2. Hotel reservation success
    saga.execute_step("ReserveHotel")
    assert hotel_service.is_reserved("hotel456")

    # 3. On payment failure the saga triggers compensation automatically
    with pytest.raises(PaymentFailedException):
        saga.execute_step("ChargePayment")

    # 4. Verify the compensation the orchestrator ran on failure
    assert saga.status == "compensated"
    assert not hotel_service.is_reserved("hotel456")  # cancelled
    assert not flight_service.is_reserved("flight123")  # cancelled

Projection Verification Harness (L5)

# harness/projection_test.py
def test_projection_consistency():
    """Verify event sourcing projection accuracy"""
    # AccountBalanceView.source = [AccountOpened, MoneyDeposited, MoneyWithdrawn]
    # 1. Create events
    events = [
        AccountOpenedEvent(accountId="A1", balance=1000),
        MoneyDepositedEvent(accountId="A1", amount=500),
        MoneyWithdrawnEvent(accountId="A1", amount=200),
    ]

    # 2. Store events
    for event in events:
        event_store.append(event)

    # 3. Update projection
    projection_service.rebuild("AccountBalanceView")

    # 4. Verify Read Model
    balance_view = read_db.get_account_balance("A1")
    assert balance_view.balance == 1300  # 1000 + 500 - 200
    assert balance_view.version == 3

Harness Priority Guide

P0 (Required)

Project failure results in data loss or serious business impact

• Example: Compensating transaction verification, event schema verification

P1 (Strongly Recommended)

Project failure results in service outage or user experience degradation

• Example: Timeout/retry, idempotency verification

P2 (Optional)

Quality improvement or operational convenience

• Example: Performance tests, chaos engineering

CI/CD Integration

Automation Pipeline

aidlc-cli is not a published tool; it is a placeholder for the ontology, harness and quality-gate validator that your organization must implement. No public CLI with this name was found (as of 2026-10-29), and the commands and options below are examples of the interface that validator should provide. Each GitHub Actions job runs on a separate runner, so for the quality-gate job to read the harness results, the run-harness job must upload the result files as an artifact and the quality-gate job must download them. needs: passes only the execution order and whether the earlier jobs succeeded.

# .github/workflows/aidlc-validation.yml
name: AIDLC Validation

on: [push, pull_request]

jobs:
  validate-ontology:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Validate Ontology
        run: |
          aidlc-cli validate-ontology --path ontology/

  run-harness:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Run Harness Tests
        run: |
          aidlc-cli run-harness --suite saga --output harness-results/saga.json
          aidlc-cli run-harness --suite idempotency --output harness-results/idempotency.json
      - name: Upload Harness Results
        uses: actions/upload-artifact@v4
        with:
          name: harness-results
          path: harness-results/

  quality-gate:
    runs-on: ubuntu-latest
    needs: [validate-ontology, run-harness]
    steps:
      - name: Download Harness Results
        uses: actions/download-artifact@v4
        with:
          name: harness-results
          path: harness-results/
      - name: Check Quality Gate
        run: |
          aidlc-cli quality-gate --threshold 80 --results harness-results/

Next Steps

• Verification Methodology: Harness verification and quality assurance
• Ontology Guide: Ontology writing methods