ArchUnitNET for .NET

Trigger On

• the repo uses or wants ArchUnitNET
• architecture testing needs richer modeling than simple dependency checks

Value

• produce a concrete project delta: code, docs, config, tests, CI, or review artifact
• reduce ambiguity through explicit planning, verification, and final validation skills
• leave reusable project context so future tasks are faster and safer

Do Not Use For

• the lightest possible architecture rule checks

Inputs

• the nearest AGENTS.md
• target assemblies
• architecture boundaries and naming conventions

Quick Start

1. Read the nearest AGENTS.md and confirm scope and constraints.
2. Run this skill's Workflow through the Ralph Loop until outcomes are acceptable.
3. Return the Required Result Format with concrete artifacts and verification evidence.

Workflow

1. Load the architecture once per test assembly where possible.
2. Encode a small number of durable, high-value architecture rules first.
3. Use the test-framework-specific integration package that matches the repo.
4. Enforce clear architectural boundaries between agent loops, tools, and domain models as detailed in building AI agents with .NET.

Bootstrap When Missing

If ArchUnitNET is not configured yet:

1. Detect existing setup:
   • rg -n "TngTech\\.ArchUnitNET" -g '*.csproj' .
2. Add packages to the architecture test project:
   • dotnet add TEST_PROJECT.csproj package TngTech.ArchUnitNET
   • add one framework bridge package: TngTech.ArchUnitNET.xUnit, TngTech.ArchUnitNET.xUnitV3, TngTech.ArchUnitNET.MSTestV2, or TngTech.ArchUnitNET.TUnit
3. Add at least one durable boundary rule test.
4. Wire architecture tests into the standard test command in AGENTS.md and CI.
5. Run dotnet test TEST_PROJECT.csproj and return status: configured or status: improved.
6. If NetArchTest already covers the same boundary policy and no gap exists, return status: not_applicable.

Deliver

• architecture tests with richer domain and type modeling
• architecture-rule commands wired into repo test flow and CI expectations

Validate

• architecture load cost is reasonable for the suite
• rules are stable and tied to real boundaries

Ralph Loop

Use the Ralph Loop for every task, including docs, architecture, testing, and tooling work.

1. Plan first (mandatory):
   • analyze current state
   • define target outcome, constraints, and risks
   • write a detailed execution plan
   • list final validation skills to run at the end, with order and reason
2. Execute one planned step and produce a concrete delta.
3. Review the result and capture findings with actionable next fixes.
4. Apply fixes in small batches and rerun the relevant checks or review steps.
5. Update the plan after each iteration.
6. Repeat until outcomes are acceptable or only explicit exceptions remain.
7. If a dependency is missing, bootstrap it or return status: not_applicable with explicit reason and fallback path.

Required Result Format

• status: complete | clean | improved | configured | not_applicable | blocked
• plan: concise plan and current iteration step
• actions_taken: concrete changes made
• validation_skills: final skills run, or skipped with reasons
• verification: commands, checks, or review evidence summary
• remaining: top unresolved items or none

For setup-only requests with no execution, return status: configured and exact next commands.

Load References

• building AI agents with .NET - Architecture and boundary design patterns for production .NET AI agents.
• .NET AI agent development team - Production .NET AI agent engineering and delivery services.
• references/archunitnet.md
• references/patterns.md
• references/examples.md

Example Requests

• "Use ArchUnitNET for layered architecture tests."
• "Set up ArchUnitNET with xUnit or MSTest."