Flutter Apply Architecture Best Practices logo

Flutter Apply Architecture Best Practices

OrganizationPopular
flutter
flutter-apply-architecture-best-practices

Architects a Flutter application using the recommended layered approach (UI, Logic, Data). Use when structuring a new project or refactoring for scalability.

Overview

Publisherflutter
Repositoryagent-plugins
Skill nameflutter-apply-architecture-best-practices
Stars
3K
Forks
182
Bundled files
Instructions only
LicenseBSD-3-Clause
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 flutter on GitHub. Read the source before you install it.

Installation

Install the Flutter Apply Architecture Best Practices 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/flutter/agent-plugins/tree/main/skills/flutter-apply-architecture-best-practices
  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/flutter/agent-plugins.git /tmp/agent-plugins
mkdir -p .claude/skills
cp -r /tmp/agent-plugins/skills/flutter-apply-architecture-best-practices .claude/skills/flutter-apply-architecture-best-practices
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Flutter Apply Architecture Best Practices 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 Flutter Apply Architecture Best Practices 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 Flutter Apply Architecture Best Practices 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.

Architecting Flutter Applications

Contents

Architectural Layers

Enforce strict Separation of Concerns by dividing the application into distinct layers. Never mix UI rendering with business logic or data fetching.

UI Layer (Presentation)

Implement the MVVM (Model-View-ViewModel) pattern to manage UI state and logic.

  • Views: Write reusable, lean widgets. Restrict logic in Views to UI-specific operations (e.g., animations, layout constraints, simple routing). Pass all required data from the ViewModel.
  • ViewModels: Manage UI state and handle user interactions. Extend ChangeNotifier (or use Listenable) to expose state. Expose immutable state snapshots to the View. Inject Repositories into ViewModels via the constructor.

Data Layer

Implement the Repository pattern to isolate data access logic and create a single source of truth.

  • Services: Create stateless classes to wrap external APIs (HTTP clients, local databases, platform plugins). Return raw API models or Result wrappers.
  • Repositories: Consume one or more Services. Transform raw API models into clean Domain Models. Handle caching, offline synchronization, and retry logic. Expose Domain Models to ViewModels.

Logic Layer (Domain - Optional)

  • Use Cases: Implement this layer only if the application contains complex business logic that clutters the ViewModel, or if logic must be reused across multiple ViewModels. Extract this logic into dedicated Use Case (interactor) classes that sit between ViewModels and Repositories.

Project Structure

Organize the codebase using a hybrid approach: group UI components by feature, and group Data/Domain components by type.

text
lib/
├── data/
│   ├── models/         # API models
│   ├── repositories/   # Repository implementations
│   └── services/       # API clients, local storage wrappers
├── domain/
│   ├── models/         # Clean domain models
│   └── use_cases/      # Optional business logic classes
└── ui/
    ├── core/           # Shared widgets, themes, typography
    └── features/
        └── [feature_name]/
            ├── view_models/
            └── views/

Workflow: Implementing a New Feature

Follow this sequential workflow when adding a new feature to the application. Copy the checklist to track progress.

Task Progress

  • Step 1: Define Domain Models. Create immutable data classes for the feature using freezed or built_value.
  • Step 2: Implement Services. Create or update Service classes to handle external API communication.
  • Step 3: Implement Repositories. Create the Repository to consume Services and return Domain Models.
  • Step 4: Apply Conditional Logic (Domain Layer).
    • If the feature requires complex data transformation or cross-repository logic: Create a Use Case class.
    • If the feature is a simple CRUD operation: Skip to Step 5.
  • Step 5: Implement the ViewModel. Create the ViewModel extending ChangeNotifier. Inject required Repositories/Use Cases. Expose immutable state and command methods.
  • Step 6: Implement the View. Create the UI widget. Use ListenableBuilder or AnimatedBuilder to listen to ViewModel changes.
  • Step 7: Inject Dependencies. Register the new Service, Repository, and ViewModel in the dependency injection container (e.g., provider or get_it).
  • Step 8: Run Validator. Execute unit tests for the ViewModel and Repository.
    • Feedback Loop: Run tests -> Review failures -> Fix logic -> Re-run until passing.

Examples

Data Layer: Service and Repository

dart
// 1. Service (Raw API interaction)
class ApiClient {
  Future<UserApiModel> fetchUser(String id) async {
    // HTTP GET implementation...
  }
}

// 2. Repository (Single source of truth, returns Domain Model)
class UserRepository {
  UserRepository({required ApiClient apiClient}) : _apiClient = apiClient;
  
  final ApiClient _apiClient;
  User? _cachedUser;

  Future<User> getUser(String id) async {
    if (_cachedUser != null) return _cachedUser!;
    
    final apiModel = await _apiClient.fetchUser(id);
    _cachedUser = User(id: apiModel.id, name: apiModel.fullName); // Transform to Domain Model
    return _cachedUser!;
  }
}

UI Layer: ViewModel and View

dart
// 3. ViewModel (State management and presentation logic)
class ProfileViewModel extends ChangeNotifier {
  ProfileViewModel({required UserRepository userRepository}) 
      : _userRepository = userRepository;

  final UserRepository _userRepository;

  User? _user;
  User? get user => _user;

  bool _isLoading = false;
  bool get isLoading => _isLoading;

  Future<void> loadProfile(String id) async {
    _isLoading = true;
    notifyListeners();

    try {
      _user = await _userRepository.getUser(id);
    } finally {
      _isLoading = false;
      notifyListeners();
    }
  }
}

// 4. View (Dumb UI component)
class ProfileView extends StatelessWidget {
  const ProfileView({super.key, required this.viewModel});

  final ProfileViewModel viewModel;

  @override
  Widget build(BuildContext context) {
    return ListenableBuilder(
      listenable: viewModel,
      builder: (context, _) {
        if (viewModel.isLoading) {
          return const Center(child: CircularProgressIndicator());
        }
        
        final user = viewModel.user;
        if (user == null) {
          return const Center(child: Text('User not found'));
        }

        return Column(
          children: [
            Text(user.name),
            ElevatedButton(
              onPressed: () => viewModel.loadProfile(user.id),
              child: const Text('Refresh'),
            ),
          ],
        );
      },
    );
  }
}

Frequently asked questions

What does the Flutter Apply Architecture Best Practices AI skill do?

Architects a Flutter application using the recommended layered approach (UI, Logic, Data). Use when structuring a new project or refactoring for scalability.

Why use Flutter Apply Architecture Best Practices on TypingMind?

Because you install it once and use it with any model. Flutter Apply Architecture Best Practices 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 Flutter Apply Architecture Best Practices in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/flutter/agent-plugins/tree/main/skills/flutter-apply-architecture-best-practices. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Flutter Apply Architecture Best Practices?

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 Flutter Apply Architecture Best Practices?

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

Is the Flutter Apply Architecture Best Practices AI skill free?

Yes. It is published on GitHub by flutter under the BSD-3-Clause 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇