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Exp Mock Usage Analysis

OrganizationPopular
dotnet
exp-mock-usage-analysis

Audits .NET test mock usage by tracing each mock setup through the production code's execution path to find dead, unreachable, redundant, or replaceable mocks. Use when the user asks to audit mock usage, find unused or unnecessary mock setups, check if mocks are needed, reduce mock duplication or over-mocking, simplify test setup, or review whether mock configurations like ILogger/IOptions should use real implementations instead. Supports Moq, NSubstitute, and FakeItEasy.

Overview

Publisherdotnet
Repositoryskills
Skill nameexp-mock-usage-analysis
Stars
5.4K
Forks
416
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 dotnet on GitHub. Read the source before you install it.

Installation

Install the Exp Mock Usage Analysis 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/dotnet/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/dotnet-experimental/skills/exp-mock-usage-analysis .claude/skills/exp-mock-usage-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Exp Mock Usage Analysis 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 Exp Mock Usage Analysis 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 Exp Mock Usage Analysis 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.

Mock Usage Analysis

Trace each mock setup through the production code's execution path to determine which setups are actually exercised at runtime and which are dead, unreachable, redundant, or replaceable with real implementations.

When to Use

  • User asks to audit, review, or analyze mock usage in .NET tests
  • User wants to find unused, unnecessary, or redundant mock setups
  • User wants to simplify test setup or reduce over-mocking
  • User asks whether mocks of ILogger, IOptions, or similar types are needed

When Not to Use

  • User wants to write new mocks or tests (general testing guidance)
  • User wants to detect non-mock test anti-patterns (use test-anti-patterns)
  • User wants to migrate between mock frameworks (out of scope)

Inputs

InputRequiredDescription
Test codeYesTest files to analyze
Production codeYesCode under test — essential for tracing execution paths

Workflow

Step 1: Read all provided code

Read the test files and always read the production code. You cannot determine whether a mock setup is necessary without understanding the production method's control flow.

Identify the mock framework by scanning for its patterns:

  • Moq: new Mock<T>(), .Setup(...), .Verify(...)
  • NSubstitute: Substitute.For<T>(), .Returns(...), .Received(...)
  • FakeItEasy: A.Fake<T>(), A.CallTo(...), .MustHaveHappened()

Use the correct framework's terminology throughout your analysis.

Step 2: Trace each mock setup through the production code

For each test method, do the following:

  1. Identify every mock setup line (.Setup, .Returns, A.CallTo, etc.)
  2. Read the production method being tested and trace its execution path for the specific inputs used in that test
  3. Determine which mock setups are actually reached during execution
  4. Classify each setup:
ClassificationMeaningExample
UsedThe production code calls this mock during the test's execution pathGetStock setup when Reserve is called and stock is sufficient
UnreachableThe production code returns early, throws, or branches away before reaching this mock callUpdateStock setup when the test expects the method to throw ArgumentOutOfRangeException on the first line
UnusedThe mock method is never called by the production method under test at all, regardless of inputsGetLowStockProducts setup when testing Reserve, which never calls that method
RedundantIdentical mock configurations are duplicated across multiple tests instead of being sharedFive tests each creating new Mock<IPaymentGateway>() with the same default setup

Pay special attention to:

  • Early returns and guard clauses — setups for mocks called after a guard clause are unreachable when the guard triggers
  • Exception throws — if the method throws before using dependencies, all setups for those dependencies are unnecessary
  • Branch-specific logic — if a method dispatches by channel/type, setups for other channels are unused
  • Verify-only tests — tests that only call .Verify/.Received/.MustHaveHappened without asserting on the method's return value

Step 3: Check for replaceable mocks

Flag mocks of stable framework types that should use real implementations:

  • Mock<ILogger<T>>NullLogger<T>.Instance (unless log output is asserted)
  • Mock<IOptions<T>>Options.Create(new T { ... })
  • Mocks of DTOs, records, or value objects → use new T { ... } directly

Explicitly confirm which mocks are correctly placed — external boundaries (databases, HTTP clients, message queues, third-party APIs) and security-sensitive types should remain mocked.

Step 4: Report findings

For each finding, state:

  1. The specific test method and mock setup line
  2. Why the setup is unnecessary (trace the production code path to explain)
  3. A concrete fix — which lines to remove, what to replace them with, or how to extract shared setup

When multiple tests duplicate mock configurations, provide a before/after example showing how to extract shared setup into a fixture or helper method.

Validation

  • Production code was read and execution paths were traced (not just test code reviewed)
  • Every finding references a specific test method and setup line
  • Unreachable setups include an explanation of which production code path makes them unreachable
  • Correctly-placed mocks (external boundaries) are explicitly noted as appropriate
  • Correct framework terminology is used throughout (not mixing Moq/NSubstitute/FakeItEasy terms)

Common Pitfalls

PitfallSolution
Analyzing test code without reading production codeAlways read the production method to trace which mocks are actually called
Flagging mocks for external boundaries (HTTP, DB)These are valid isolation boundaries — keep them mocked
Flagging ILogger mock when log output is assertedOnly flag when the mock is set up but log output is never verified
Using wrong framework terminologyMatch the framework in the code: Moq (Setup/Verify), NSubstitute (Returns/Received), FakeItEasy (A.CallTo/MustHaveHappened)

Frequently asked questions

What does the Exp Mock Usage Analysis AI skill do?

Audits .NET test mock usage by tracing each mock setup through the production code's execution path to find dead, unreachable, redundant, or replaceable mocks. Use when the user asks to audit mock usage, find unused or unnecessary mock setups, check if mocks are needed, reduce mock duplication or over-mocking, simplify test setup, or review whether mock configurations like ILogger/IOptions should use real implementations instead. Supports Moq, NSubstitute, and FakeItEasy.

Why use Exp Mock Usage Analysis on TypingMind?

Because you install it once and use it with any model. Exp Mock Usage Analysis 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 Exp Mock Usage Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dotnet/skills/tree/main/plugins/dotnet-experimental/skills/exp-mock-usage-analysis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Exp Mock Usage Analysis?

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 Exp Mock Usage Analysis?

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

Is the Exp Mock Usage Analysis AI skill free?

Yes. It is published on GitHub by dotnet 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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