Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add managedcode/dotnet-skills --skill archunitnetgit clone --depth 1 https://github.com/managedcode/dotnet-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/managedcode/dotnet-skills/archunitnet)<a href="https://agentmods.dev/skills/managedcode/dotnet-skills/archunitnet"><img src="https://agentmods.dev/badge/skills/managedcode/dotnet-skills/archunitnet/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/managedcode/dotnet-skills/archunitnet"><img src="https://agentmods.dev/badge/skills/managedcode/dotnet-skills/archunitnet.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00104 | $0.01097 |
| Opus 5.5 | $0.00042 | $0.00439 |
| Sonnet 5.5 | $0.00021 | $0.00219 |
| Haiku 4.5 | $0.00010 | $0.00110 |
Grade A, and why
archunitnet scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
4 near-identical copies found in the catalogue:
- dotnet-archunitnet — 92% identical, 15 lines differ
- archunitnet — 89% identical, 11 lines differ
- mcaf-dotnet-archunitnet — 88% identical, 13 lines differ
- mcaf-dotnet-archunitnet — 88% identical, 13 lines differ
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Read the nearest
AGENTS.mdand confirm scope and constraints. - Run this skill's
Workflowthrough theRalph Loopuntil outcomes are acceptable. - Return the
Required Result Formatwith concrete artifacts and verification evidence.
Workflow
- Load the architecture once per test assembly where possible.
- Encode a small number of durable, high-value architecture rules first.
- Use the test-framework-specific integration package that matches the repo.
- 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:
- Detect existing setup:
rg -n "TngTech\\.ArchUnitNET" -g '*.csproj' .
- 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, orTngTech.ArchUnitNET.TUnit
- Add at least one durable boundary rule test.
- Wire architecture tests into the standard
testcommand inAGENTS.mdand CI. - Run
dotnet test TEST_PROJECT.csprojand returnstatus: configuredorstatus: improved. - If
NetArchTestalready covers the same boundary policy and no gap exists, returnstatus: not_applicable.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed · +3 lines 5fb6b3d70ded
- 1mo ago First seen · 104 lines · 104 tokens per session scan A a78a5ee4c1c6
archunitnet is a skill published in the GitHub repository managedcode/dotnet-skills (492 stars, last pushed yesterday), licensed MIT. It adds 104 tokens to every session and 1,097 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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