mcpbeat Sign in

Nw Hexagonal Testing Skill for Claude

5-layer agent output validation, I/O contract specification, vertical slice development, and test doubles policy with per-layer examples

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
588
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/nWave-ai/nWave --skill nw-hexagonal-testing

The instruction itself

15 sections, as written by the author

Hexagonal Testing and Output Validation

5-Layer Output Validation Framework

Validates agent OUTPUTS, not TDD testing methodology.

Layer 1: Unit Testing (Output Validation)

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'"

Layer 2: Integration Testing (Handoff Validation)

Validate handoffs to next agent. Next agent must consume outputs without clarification.

  • Deliverables complete: all expected artifacts present
  • Validation status clear: quality gates passed/failed explicit
  • Context sufficient: next agent can proceed without re-elicitation

Layer 3: Adversarial Output Validation

Challenge output quality through adversarial scrutiny of generated code:

  • SQL injection vulnerabilities? | XSS vulnerabilities? | Null/undefined/empty input handling?
  • Integer overflow/underflow? | Graceful failure vs crash? | Exception handling appropriateness?

Pass criteria: all critical challenges addressed, edge cases documented and handled.

For peer review and escalation protocols, load the review-dimensions skill.

Input/Output Contract

Inputs

  • Required: user_request (non-empty command string) | context_files (existing readable file paths)
  • Optional: configuration (YAML/JSON) | previous_artifacts (outputs from prior wave for handoff)

Outputs

  • Primary: code artifacts (src/**/*, strictly necessary only) | documentation (docs/develop/, minimal essential)
  • Secondary: validation_results (gate pass/fail status) | handoff_package (deliverables, next_agent, validation_status)
  • Policy: any document beyond code/test files requires explicit user approval before creation

Side Effects

  • Allowed: file creation (src/, tests/ only) | file modification with audit trail | log entries
  • Forbidden: unsolicited documentation | deletion without approval | external API calls | credential access
  • Requires permission: documentation beyond code/test files | summary reports | analysis documents

Error Handling

  • Invalid input: validate first, clear error, do not proceed with partial inputs
  • Processing error: log context, return to safe state, actionable user message
  • Validation failure: report failed gates, withhold artifacts, suggest remediation

Vertical Slice Development

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.

Testing Boundaries per Architectural Layer

| 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 |

Key Insight

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.

Integration Surface Ratio Heuristic

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.

Strategy D Fixture Template

# 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.

Other skills for the same job

different authors, same section of the catalogue
Webapp Testing
by anthropics
vendor ×12

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

6k tokens scripts
Finishing A Development Branch
by ZhanlinCui
×7

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

1k tokens
Test Driven Development
by w95
×7

Use when implementing any feature or bugfix, before writing implementation code

2k tokens
Systematic Debugging
by ratacat
×7

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

10k tokens scripts
Verification Before Completion
by ZhanlinCui
×6

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

1k tokens
Backtest Expert
by BaggaT236
×3

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

15k tokens scripts
Adaptyv
by christophacham
×3

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

16k tokens
Aeon
by christophacham
×3

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

19k tokens

How to use it

Copy the folder

Take nwave-ai/nw-hexagonal-testing from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.