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Architecture Feature First

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evanca
architecture-feature-first

Use when creating a feature, designing folder structure, adding repositories/services/view models, wiring dependency injection, or deciding which layer owns logic.

Overview

Publisherevanca
Repositoryflutter-ai-rules
Skill namearchitecture-feature-first
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 Architecture Feature First 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/architecture-feature-first
  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/architecture-feature-first .claude/skills/architecture-feature-first
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Architecture Feature First 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 Architecture Feature First 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 Architecture Feature First 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.

Flutter Architecture — Feature-First Skill

This skill defines how to design, structure, and implement Flutter applications using the recommended layered architecture with feature-first file organization.

It is state management agnostic: the business logic holder in the UI layer may be named ViewModel, Controller, Cubit, Bloc, Provider, or Notifier — depending on the chosen state management approach. The architectural rules apply equally to all of them.

When to Use

Use this skill when:

  • Designing the folder/file structure of a new Flutter app or feature.
  • Creating a new View, ViewModel, Repository, or Service.
  • Deciding which layer owns a piece of logic.
  • Wiring dependency injection between components.
  • Adding a domain (logic) layer for complex business logic.
  • Refactoring an existing app from type-first to feature-first organization.

1. Layers

Separate every app into a UI Layer and a Data Layer. Add a Logic (Domain) Layer between them only for complex apps.

┌──────────────────────────────────────────────────────────────┐
│   UI Layer    │  Views + business logic holders              │
│               │  (ViewModel / Cubit / Controller / Provider) │
├──────────────────────────────────────────────────────────────┤
│  Logic Layer  │  Use Cases / Interactors  (optional)         │
├──────────────────────────────────────────────────────────────┤
│   Data Layer  │  Repositories + Services                     │
└──────────────────────────────────────────────────────────────┘

Rules:

  • Only adjacent layers may communicate. The UI layer must never access a Service directly.
  • The Logic layer is added only when business logic is too complex for the business logic holder or is reused across multiple screens.
  • Data changes always happen in the Data layer (SSOT = Repository). No mutation in UI or Logic layers.
  • Follow unidirectional data flow: state flows down (Data → UI), events flow up (UI → Data).

2. Feature-First File Structure

Organize code by feature, not by type. Group all layers belonging to one feature together in a single directory.

Sample directory structure

lib/
├── app.dart
├── main.dart
├── core/                          # Shared utilities, theme, DI setup
│   ├── di/
│   │   └── service_locator.dart
│   ├── theme/
│   │   └── app_theme.dart
│   └── network/
│       └── api_client.dart
├── features/
│   ├── auth/
│   │   ├── data/
│   │   │   ├── auth_repository.dart
│   │   │   └── auth_api_service.dart
│   │   ├── domain/                # Optional — only for complex logic
│   │   │   └── login_usecase.dart
│   │   └── ui/
│   │       ├── auth_viewmodel.dart
│   │       ├── login_screen.dart
│   │       └── widgets/
│   │           └── login_form.dart
│   └── profile/
│       ├── data/
│       │   ├── profile_repository.dart
│       │   └── profile_api_service.dart
│       └── ui/
│           ├── profile_viewmodel.dart
│           └── profile_screen.dart
└── shared/                        # Shared widgets, models, extensions
    ├── models/
    │   └── user.dart
    └── widgets/
        └── loading_indicator.dart

Each feature directory contains the files needed for that feature, named according to the chosen state management approach:

ApproachBusiness logic holder file
MVVM / ChangeNotifier*_viewmodel.dart / *_controller.dart
BLoC*_cubit.dart / *_bloc.dart
Provider / Riverpod*_provider.dart / *_notifier.dart

3. Component Responsibilities

View

  • Describes how to present data to the user; keep logic minimal and only UI-related.
  • Passes events to the business logic holder in response to user interactions.
  • Extract reusable widgets into separate components within a widgets/ subdirectory.
  • Use StatelessWidget when possible; keep build methods simple.

Business Logic Holder (ViewModel / Cubit / Controller / Provider)

  • Contains logic to convert app data into UI state and maintains current state needed by the view.
  • Exposes callbacks (commands) to the View and retrieves/transforms data from repositories.
dart
class AuthViewModel extends ChangeNotifier {
  final AuthRepository _authRepo;
  AuthViewModel(this._authRepo);

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

  String? _error;
  String? get error => _error;

  Future<bool> login(String email, String password) async {
    _isLoading = true;
    _error = null;
    notifyListeners();
    try {
      await _authRepo.login(email, password);
      return true;
    } catch (e) {
      _error = e.toString();
      return false;
    } finally {
      _isLoading = false;
      notifyListeners();
    }
  }
}

Repository

  • Single Source of Truth (SSOT) for a given type of model data.
  • The only class allowed to mutate its data; all other classes read from it.
  • Handles caching, error handling, and data refresh logic.
  • Transforms raw data from services into domain models.

Service

  • Wraps API endpoints and exposes asynchronous response objects.
  • Isolates data-loading and holds no state.

4. Domain Layer (Use Cases)

Introduce use cases/interactors only when:

  • Logic is complex or does not fit cleanly in the UI or Data layers.
  • Logic is reused across multiple business logic holders or merges data from multiple repositories.

Do not add a domain layer for simple CRUD apps.


5. Dependency Injection

Use dependency injection to provide components with their dependencies, enabling testability and flexibility.

  • Supply repositories to business logic holders via constructors.
  • Supply services to repositories via constructors.
  • Define abstract interfaces so implementations can be swapped without changing consumers.
dart
// In service_locator.dart — register dependencies at startup
void setupDependencies() {
  final apiClient = ApiClient();

  // Services
  final authService = AuthApiService(apiClient);
  final profileService = ProfileApiService(apiClient);

  // Repositories
  final authRepo = AuthRepository(authService);
  final profileRepo = ProfileRepository(profileService);

  // Register with your DI framework (get_it, provider, riverpod, etc.)
  getIt.registerSingleton<AuthRepository>(authRepo);
  getIt.registerSingleton<ProfileRepository>(profileRepo);
}

6. Workflow: Add a New Feature

  1. Create the features/<name>/ directory with data/, ui/, and optionally domain/ subdirectories.
  2. Implement the Service — wrap the API endpoints in data/<name>_api_service.dart.
  3. Implement the Repository — inject the Service, add caching/error handling in data/<name>_repository.dart.
  4. Implement the ViewModel — inject the Repository, expose UI state and commands in ui/<name>_viewmodel.dart.
  5. Implement the View — bind to the ViewModel, render state, dispatch events in ui/<name>_screen.dart.
  6. Register in DI — add the new Service, Repository, and ViewModel to the service locator.
  7. Verify — confirm the View never accesses the Service directly and data flows unidirectionally.

References

Frequently asked questions

What does the Architecture Feature First AI skill do?

Use when creating a feature, designing folder structure, adding repositories/services/view models, wiring dependency injection, or deciding which layer owns logic.

Why use Architecture Feature First on TypingMind?

Because you install it once and use it with any model. Architecture Feature First 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 Architecture Feature First in TypingMind?

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

Which AI models can use Architecture Feature First?

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 Architecture Feature First?

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

Is the Architecture Feature First 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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