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Mstest

Organization
managedcode
mstest

Write, run, or repair .NET tests that use MSTest. Use when a repo uses `MSTest.Sdk`, `MSTest`, `[TestClass]`, `[TestMethod]`, `DataRow`, or Microsoft.Testing.Platform-based MSTest execution. USE FOR: the repo uses MSTest; you need to add, run, debug, or repair MSTest tests; the repo is moving between VSTest and Microsoft.Testing.Platform. DO NOT USE FOR: xUnit projects; TUnit projects. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

Overview

Publishermanagedcode
Repositorydotnet-skills
Skill namemstest
Stars
492
Forks
38
Bundled files
4
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Mstest 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.
    https://github.com/managedcode/dotnet-skills/tree/main/catalog/Testing/MSTest/skills/mstest
  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/managedcode/dotnet-skills.git /tmp/dotnet-skills
mkdir -p .claude/skills
cp -r /tmp/dotnet-skills/catalog/Testing/MSTest/skills/mstest .claude/skills/mstest
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mstest 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 Mstest 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 Mstest 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.

MSTest

Diagnostic Output Budget

Keep native test progress and ANSI visible; use the detected runner's supported flags (--progress on --ansi on for MTP/TUnit), not MTP switches on VSTest. Keep console logs at Warning or higher and one concise final summary. Do not replay progress redraws, successful-test output, or Information/Debug/Trace logs into model context. On failure/crash, show only the failing test/resource, root error, and relevant stack frames; deduplicate and cap each diagnostic response at 80 lines / 8 KiB. Never dump entire console/host/browser logs, HTML, TRX, or crash artifacts. Keep necessary artifacts size-bounded outside context, link them, and inspect exact bounded excerpts. Preserve the runner exit code through capture/filtering; disclose truncation. Silence alone does not establish a hang.

Trigger On

  • the repo uses MSTest
  • you need to add, run, debug, or repair MSTest tests
  • the repo is moving between VSTest and Microsoft.Testing.Platform

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

  • xUnit projects
  • TUnit projects
  • generic test strategy with no MSTest-specific mechanics

Inputs

  • the nearest AGENTS.md
  • the test project file and package references
  • the active MSTest runner model

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. Detect the MSTest project style first:
    • MSTest.Sdk project SDK
    • MSTest meta-package
    • legacy package set with explicit Microsoft.NET.Test.Sdk
  2. Read the repo's real test command from AGENTS.md. If the repo has no explicit command yet, start with dotnet test PROJECT_OR_SOLUTION.
  3. Keep the runner model consistent:
    • MSTest.Sdk defaults to the MSTest runner on Microsoft.Testing.Platform
    • VSTest is opt-in with UseVSTest=true or legacy package choices
    • do not pass VSTest-only switches or assume legacy .runsettings behavior on Microsoft.Testing.Platform jobs
  4. Prefer [DataRow] or DynamicData for stable data-driven coverage. Keep test lifecycle hooks minimal and deterministic.
  5. Keep MSTest analyzers enabled and fix findings instead of muting them casually.
  6. Align coverage/reporting packages with the active runner.

Bootstrap When Missing

If MSTest is requested but not configured:

  1. Detect current framework first:
    • rg -n "MSTest\\.Sdk|PackageReference Include=\"MSTest\"|xunit|TUnit|UseVSTest|TestingPlatformDotnetTestSupport" -g '*.csproj' .
  2. If the repo currently uses xUnit or TUnit, do not auto-migrate. Return status: not_applicable unless migration is explicitly requested.
  3. For explicit MSTest adoption, add package(s) to target test project:
    • dotnet add TEST_PROJECT.csproj package MSTest
  4. Document runner model (MSTest.Sdk default MTP vs UseVSTest) in AGENTS.md.
  5. Run dotnet test TEST_PROJECT.csproj and return status: configured or status: improved.

Deliver

  • MSTest tests that match the repo's runner model
  • commands that work in local and CI runs
  • explicit guidance for VSTest versus Microsoft.Testing.Platform usage

Validate

  • the runner model is documented and consistent
  • test commands match that runner
  • data-driven tests stay deterministic
  • analyzer, coverage, and reporting packages align with the chosen runner

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

Example Requests

  • "Fix our MSTest runner setup."
  • "Add an MSTest regression test."
  • "Move this MSTest project to Microsoft.Testing.Platform safely."

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mstest AI skill do?

Write, run, or repair .NET tests that use MSTest. Use when a repo uses `MSTest.Sdk`, `MSTest`, `[TestClass]`, `[TestMethod]`, `DataRow`, or Microsoft.Testing.Platform-based MSTest execution. USE FOR: the repo uses MSTest; you need to add, run, debug, or repair MSTest tests; the repo is moving between VSTest and Microsoft.Testing.Platform. DO NOT USE FOR: xUnit projects; TUnit projects. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

Why use Mstest on TypingMind?

Because you install it once and use it with any model. Mstest 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 Mstest in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/managedcode/dotnet-skills/tree/main/catalog/Testing/MSTest/skills/mstest. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mstest?

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 Mstest?

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

Is the Mstest AI skill free?

Yes. It is published on GitHub by managedcode 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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