nw-ab-critique-dimensi…
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
5-layer agent output validation, I/O contract specification, vertical slice development, and test doubles policy with per-layer examples
$ npx -y skills add nWave-ai/nWave --skill nw-hexagonal-testing --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nw-hexagonal-testingContext preview
The summary Claude sees to decide when to auto-load this skill.
5-layer agent output validation, I/O contract specification, vertical slice development, and test doubles policy with per-layer examples
name: nw-hexagonal-testing description: 5-layer agent output validation, I/O contract specification, vertical slice development, and test doubles policy with per-layer examples user-invocable: false disable-model-invocation: true
Validates agent OUTPUTS, not TDD testing methodology.
Validate individual software-crafter outputs.
structural_checks: - required_elements_present: true - format_compliance: true - quality_standards_met: true quality_checks: - completeness: "All required components present" - clarity: "Unambiguous and understandable" - testability: "Can be validated" test_data_quality: real_data: "Use real API responses as golden masters" edge_cases: "Test null, empty, malformed, boundary conditions" assertions: "Assert expected counts, not just 'any results'"
Validate handoffs to next agent. Next agent must consume outputs without clarification.
Challenge output quality through adversarial scrutiny of generated code:
Pass criteria: all critical challenges addressed, edge cases documented and handled.
For peer review and escalation protocols, load the review-dimensions skill.
Complete business capability per slice: UI -> Application -> Domain -> Infrastructure for a specific feature. Slices developed and deployed independently. Focus on business capability over technical layer.
For test doubles policy and violation examples, load the tdd-methodology skill.
| Layer | Test Strategy | Adapter Selection | Rationale | |-------|--------------|------------------|-----------| | Domain | Pure unit test, zero I/O | N/A (no adapters) | Domain is pure functions — test with pure inputs | | Application | InMemory ports for focused scenarios | InMemory doubles | Application orchestrates — test logic, not I/O | | Adapter | REAL I/O ALWAYS* | Real system (tmp_path, subprocess, DB) | Adapter IS the I/O boundary — testing with InMemory defeats the purpose |
*Exception: costly subprocesses (claude -p, LLM) and paid external APIs use contract smoke tests tagged `@requires_external` instead of real I/O. See nw-tdd-methodology Mandate 6 for the full adapter type → test type table. | WS/E2E | Per declared strategy (A/B/C/D) | Real for local, fake for costly | WS proves wiring — InMemory proves nothing about wiring |
A pure function stub at a driven port boundary models the port's CONTRACT, not the external system's BEHAVIOR. For every driven port stub, verify that an adapter integration test with real I/O covers the behavioral gap.
If the system's primary job is coordinating external processes (orchestrators, ETL, deployment scripts), invest MORE in WS and adapter integration tests than unit tests. If the system's primary job is domain computation (pricing, validation, parsing), the traditional pyramid applies.
# conftest.py
import os
import pytest
@pytest.fixture
def subprocess_runner():
"""Returns real or fake subprocess runner based on E2E mode."""
if os.getenv("NWAVE_E2E_REAL_SUBPROCESS") == "1":
from myapp.adapters.real_subprocess_runner import RealSubprocessRunner
return RealSubprocessRunner()
from tests.doubles.fake_subprocess_runner import FakeSubprocessRunner
return FakeSubprocessRunner(exit_code=0, stdout="OK")Naming convention for multi-port Strategy D: `NWAVE_E2E_REAL_{PORT_NAME}` per driven port (e.g., `NWAVE_E2E_REAL_SUBPROCESS`, `NWAVE_E2E_REAL_DATABASE`). Use `NWAVE_E2E_MODE=real` as composite flag to enable ALL real adapters at once for full E2E.
AI agents that guide you from idea to working code, with human judgment at every gate. nWave runs inside Claude Code. It breaks feature delivery into seven waves (discover, diverge, discuss, design, devops, distill, deliver).
Repo: nWave-ai/nWave
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
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