Arch Check logo

Arch Check

Organization
codewithmukesh
arch-check

Architecture conformance check: verifies an existing codebase against its declared architecture (VSA, Clean Architecture, DDD, Modular Monolith) — dependency direction, layer violations, module boundary leaks, and cycles — using token-cheap Roslyn MCP analysis. Invoke when: "check architecture", "architecture violations", "layer violations", "dependency direction", "module boundaries", "arch check", "is my architecture clean", "enforce architecture", "conformance check". For CHOOSING an architecture, use architecture-advisor instead.

Overview

Publishercodewithmukesh
Repositorydotnet-claude-kit
Skill namearch-check
Stars
721
Forks
170
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by codewithmukesh on GitHub. Read the source before you install it.

Installation

Install the Arch Check AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/codewithmukesh/dotnet-claude-kit.git /tmp/dotnet-claude-kit
mkdir -p .claude/skills
cp -r /tmp/dotnet-claude-kit/skills/arch-check .claude/skills/arch-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Arch Check in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Arch Check on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Arch Check is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/arch-check

What

Verifies that the code still matches the architecture it claims to have. Architectures rot through small, individually-reasonable changes — a Domain project that gains an EF Core reference, a module that reaches into a sibling's internals, an endpoint defined outside the host. This workflow catches the rot using project-graph and dependency analysis, not file-by-file reading.

Output: a violation report with severity, file:line evidence, and the concrete fix — or a clean conformance pass.

When

  • "check my architecture", "are there layer violations", "dependency direction"
  • Before a release or after a large feature lands
  • After onboarding to an unfamiliar codebase that claims an architecture
  • Recurring on teams where multiple people merge to shared modules
  • NOT for choosing an architecture — that is architecture-advisor

How

Step 1: Establish the declared architecture

In order of authority: the project's CLAUDE.md, an ADR in docs/decisions/, or ask the user. Never infer silently — a wrong baseline produces a wrong report. The four supported baselines and their rules:

ArchitectureRules checked
Vertical SliceFeatures don't reference sibling features; shared code only via explicitly shared folders/projects
Clean ArchitectureDomain → nothing; Application → Domain only; Infrastructure → Application; Api → Application (never Api → Infrastructure types, wiring only)
DDD + CleanClean rules + aggregates referenced only via roots; domain events for cross-aggregate effects
Modular MonolithNo project references between modules except *.Contracts; cross-module calls via integration events or contracts

Step 2: Project-level dependency direction (cheapest, catches most)

get_project_graph()

Map every project reference against the baseline's allowed arrows. A single wrong reference here (Domain → Infrastructure) is a CRITICAL finding — it makes every downstream violation possible.

Step 3: Cycles

detect_circular_dependencies()

Cycles are violations in every baseline. Report the full chain.

Step 4: Namespace-level leaks (spot checks)

Project references can be clean while code still leaks. Probe the risky edges:

get_dependency_graph(symbolName: <a Domain entity>, depth: 2)
   -- Domain types pulling in EF Core, HttpClient, or Infrastructure namespaces?
find_references(symbolName: <a module-internal type>)
   -- referenced from outside its module?
detect_antipatterns()
   -- known structural smells as supporting evidence

Pick probes by baseline: Clean → sample 3-5 Domain entities and Application handlers; Modular Monolith → sample each module's internal types; VSA → sample types inside two or three feature folders.

Step 5: Presentation boundary

get_endpoint_map()

Endpoints must live only in the host/Api layer (Clean) or inside their owning module (Modular Monolith, VSA feature folders). An endpoint defined in an Application or shared project is a boundary violation. Unmarked auth on any endpoint is reported as a side-finding (route to /security-scan for depth).

Step 6: Report

SeverityMeaning
CRITICALWrong-direction project reference, module-to-module reference, cycle
HIGHNamespace leak (Domain using Infrastructure/EF types), endpoint outside its layer
MEDIUMShared-kernel logic creep, aggregate bypassed via direct member access
INFOUnmarked endpoint auth, antipattern hits worth a look

Each finding: evidence (file:line), why it violates the baseline, and the fix (move the code, invert with an interface, introduce a contracts project, raise an integration event). Offer to fix CRITICAL items immediately.

MCP Tools Used

  • get_project_graph — reference-direction audit (the backbone)
  • detect_circular_dependencies — cycle detection
  • get_dependency_graph / find_references — namespace-level leak probes
  • get_endpoint_map — presentation boundary + auth posture
  • detect_antipatterns — supporting structural evidence

Example

User: /arch-check

Claude: Baseline from CLAUDE.md: Clean Architecture (4 projects).

  Project graph (get_project_graph)...
  CRITICAL  Domain → Infrastructure reference (Domain.csproj:14)
            Breaks the dependency rule; makes Domain untestable in isolation.
            Fix: invert — define IEmailSender in Application, implement in
            Infrastructure.
  Cycles (detect_circular_dependencies)... none.
  Leak probes on 4 Domain entities...
  HIGH      Order.cs:8 uses Microsoft.EntityFrameworkCore (Domain must stay
            persistence-ignorant). Fix: move the [Index] config to
            OrderConfiguration in Infrastructure.
  Endpoint map... 23 endpoints, all in Api. 2 unmarked auth (side-finding —
  run /security-scan).

  Verdict: NOT conformant — 1 critical, 1 high. Fix the reference first;
  want me to do it now?

Related

  • architecture-advisor — choosing a baseline (before this skill is useful)
  • clean-architecture, vertical-slice, ddd, modular-monolith template — the rules being enforced
  • /security-scan — depth on the auth side-findings
  • /health-check — broader report card; arch-check is its architecture dimension in depth

Frequently asked questions

What does the Arch Check AI skill do?

Architecture conformance check: verifies an existing codebase against its declared architecture (VSA, Clean Architecture, DDD, Modular Monolith) — dependency direction, layer violations, module boundary leaks, and cycles — using token-cheap Roslyn MCP analysis. Invoke when: "check architecture", "architecture violations", "layer violations", "dependency direction", "module boundaries", "arch check", "is my architecture clean", "enforce architecture", "conformance check". For CHOOSING an architecture, use architecture-advisor instead.

Why use Arch Check on TypingMind?

Because you install it once and use it with any model. Arch Check is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Arch Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/codewithmukesh/dotnet-claude-kit/tree/main/skills/arch-check. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Arch Check?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Arch Check?

As many as you like. As long as a model supports skills, you can use Arch Check with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Arch Check AI skill free?

Yes. It is published on GitHub by codewithmukesh under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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