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Mockito

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evanca
mockito

Use when generating mocks, stubbing methods, verifying interactions, capturing arguments, or choosing between mocks, fakes, and real objects (Mockito).

Overview

Publisherevanca
Repositoryflutter-ai-rules
Skill namemockito
Stars
651
Forks
67
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 evanca on GitHub. Read the source before you install it.

Installation

Install the Mockito 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/evanca/flutter-ai-rules/tree/main/skills/mockito
  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/evanca/flutter-ai-rules.git /tmp/flutter-ai-rules
mkdir -p .claude/skills
cp -r /tmp/flutter-ai-rules/skills/mockito .claude/skills/mockito
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mockito 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 Mockito 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 Mockito 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.

Mockito Skill

This skill defines how to correctly use the mockito package for mocking in Dart and Flutter tests.


1. Mock vs. Fake vs. Real Object

UseWhen
Real objectPrefer over mocks when practical.
Fake (extends Fake)Lightweight custom implementation; override only the methods you need. Prefer over mocks when you don't need interaction verification.
Mock (extends Mock)Only when you need to verify interactions (call counts, arguments) or stub dynamic responses.
  • Data models should not be mocked if they can be constructed with stubbed data.
  • Only use mocks if your test has verify assertions; otherwise prefer real or fake objects.

2. Generating Mocks

dart
@GenerateMocks([MyClass])
// or for nice mocks (return simple legal values for missing stubs):
@GenerateNiceMocks([MockSpec<MyClass>()])
void main() { ... }
bash
dart run build_runner build
  • Only annotate files under test/ for mock generation by default.
  • Use a build.yaml if you need to generate mocks outside of test/.
  • Never add @override methods or implementations to a class extending Mock.
  • Never stub responses in a mock's constructor or inside the mock class — always stub in your tests.

3. Stubbing

dart
final mock = MockCat();

// Return a value
when(mock.sound()).thenReturn('Meow');

// Throw an error
when(mock.sound()).thenThrow(Exception('No sound'));

// Calculate response at call time
when(mock.sound()).thenAnswer((_) => computedValue);

// Return values in sequence
when(mock.sound()).thenReturnInOrder(['Meow', 'Purr']);
  • Always stub methods/getters before using them if you need specific return values.
  • Missing stub behavior: @GenerateMocks → throws; @GenerateNiceMocks → returns a simple legal value.
  • Use throwOnMissingStub(mock) to throw on any unstubbed call.

4. Verification

dart
verify(mock.sound());                  // called at least once
verifyNever(mock.eat(any));            // never called
verify(mock.sound()).called(2);        // called exactly twice

Async:

dart
await untilCalled(mock.sound());       // wait for the interaction

5. Argument Matchers

dart
// Flexible stubbing
when(mock.eat(any)).thenReturn(true);
when(mock.eat(argThat(isNotNull))).thenReturn(true);

// Named arguments
when(mock.fetch(any, headers: any)).thenReturn(response);
  • Do not use null as an argument adjacent to an argument matcher.
  • For named arguments, use any or argThat as values, not as argument names.

6. Capturing Arguments

dart
final captured = verify(mock.eat(captureAny)).captured;
print(captured.last); // last captured argument

Use captureThat for conditional capturing.


7. Resetting Mocks

dart
reset(mock);                  // clear all stubs AND interactions
clearInteractions(mock);      // clear only recorded interactions

8. Mocking Function Types

To mock a function type (e.g., a callback), define an abstract class with the required signature and generate mocks for it:

dart
abstract class Callback {
  void call(String value);
}

@GenerateMocks([Callback])

9. Debugging

dart
logInvocations([mock1, mock2]); // print all collected invocations

References

Frequently asked questions

What does the Mockito AI skill do?

Use when generating mocks, stubbing methods, verifying interactions, capturing arguments, or choosing between mocks, fakes, and real objects (Mockito).

Why use Mockito on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/evanca/flutter-ai-rules/tree/main/skills/mockito. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Mockito?

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 Mockito?

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

Is the Mockito AI skill free?

Yes. It is published on GitHub by evanca 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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