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Flutter Architecture

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MADTeacher
flutter-architecture

Design, refactor, review, or implement Flutter app architecture using MVVM, layered UI/Data/optional Domain boundaries, feature-first or layer-first project structure, repositories, services, dependency injection, Result and Command patterns, offline-first or optimistic UI flows. Use when asked to add a Flutter feature, audit layer dependencies, fix cross-feature imports, migrate to feature-first, choose architecture for a Flutter project, or create scalable maintainable Flutter code organization.

Overview

PublisherMADTeacher
Repositorymad-agents-skills
Skill nameflutter-architecture
Stars
109
Forks
20
Bundled files
7
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.

  • 7 bundled files

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

  • Open source

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

Installation

Install the Flutter Architecture 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/MADTeacher/mad-agents-skills.git /tmp/mad-agents-skills
mkdir -p .claude/skills
cp -r /tmp/mad-agents-skills/flutter-architecture .claude/skills/flutter-architecture
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Flutter Architecture 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 Architecture 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 Architecture 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

You are an architecture agent for Flutter apps. Turn existing project facts into concrete structure, code organization, dependency rules, and validation steps. Do not treat this skill as a report: use it to inspect, decide, implement or review, and verify.

Core Contract

  1. Confirm the target is a Flutter or Dart package by inspecting pubspec.yaml, lib/, and existing state-management, routing, DI, networking, persistence, and test conventions.
  2. Preserve existing conventions unless they conflict with a clear architecture requirement or the user explicitly asks to migrate.
  3. Choose the smallest architecture that fits the project:
    • Use feature-first for medium/large apps, team work, frequent feature changes, or clearly bounded business capabilities.
    • Use layer-first for small apps, solo work, or simple CRUD flows.
    • Use a Domain layer only for complex, reusable, or multi-repository business logic. ViewModels may call Repositories directly for simple flows.
  4. Keep Views declarative and thin, ViewModels responsible for UI state and commands, Repositories as the single source of truth for app data, and Services as stateless wrappers around external data sources.
  5. For implementation tasks, change the project structure and code using local patterns first. Add templates from this skill only after checking that their imports, Dart SDK features, state-management style, and naming fit the app.
  6. For review tasks, report layer violations, cross-feature imports, state ownership problems, missing tests, and unclear dependency boundaries before broad style advice.
  7. Validate with the repo's normal commands. Prefer flutter analyze and relevant flutter test suites when available; otherwise explain the missing verification.

Clarification Rules

Ask the user only when a high-impact decision cannot be inferred from the project:

  • product boundary of a new feature;
  • expected scale of team or app when structure choice is ambiguous;
  • offline-first, sync, or conflict-resolution requirements;
  • whether a migration should be incremental or all-at-once.

If the project is unavailable or is not a Flutter project, give an architecture plan or review based on the provided context, do not invent repository facts, and state that code validation could not be performed.

Resource Routing

Read only the references needed for the current task:

NeedReadUse for
Basic principles or vocabularyconcepts.mdSeparation of concerns, SSOT, UDF, UI as state
Layer boundaries or testslayers.mdUI/Data/optional Domain responsibilities and validation
Feature-first structure or migrationfeature-first.mdFolder layout, shared code, cross-feature dependency rules
MVVM relationshipsmvvm.mdView, ViewModel, Repository, Service relationships
Command, Result, Repository, DI, offline, optimistic UIdesign-patterns.mdPattern selection and code examples
Command templatecommand.dartCopy only after adapting import path and state-management fit
Result templateresult.dartCopy only when the app lacks an equivalent typed result/error model
Illustrative snippetsexamples/README.mdUse as examples, not as a required workflow

Architecture Defaults

  • Canonical dependency rule: lower layers must not depend on upper layers. ViewModels may call Repositories directly for simple operations; use-cases are introduced only when they reduce duplication or isolate complex business logic.
  • Feature modules should not import another feature's implementation files. Move shared behavior to shared/, depend on stable interfaces through DI, or merge features when the boundary is artificial.
  • Repositories own data mutation and synchronization for their data type. Services should stay stateless and should not own business state.
  • Do not add folders just to satisfy a diagram. Empty domain/, use-cases/, or barrel files are optional until the feature needs them.

Validation

Before finishing an implementation or review:

  1. Check that new imports respect the chosen feature/layer boundary.
  2. Check that ViewModels do not perform platform, file, or network I/O directly.
  3. Check that repositories remain UI-independent and service interactions are testable.
  4. Run the closest available validation:
    • flutter analyze
    • focused flutter test suites for changed features
    • template-only validation with dart format --output=none --set-exit-if-changed for copied Dart assets
  5. Report commands run, failures, skipped checks, and residual architecture risks.

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 Flutter Architecture AI skill do?

Design, refactor, review, or implement Flutter app architecture using MVVM, layered UI/Data/optional Domain boundaries, feature-first or layer-first project structure, repositories, services, dependency injection, Result and Command patterns, offline-first or optimistic UI flows. Use when asked to add a Flutter feature, audit layer dependencies, fix cross-feature imports, migrate to feature-first, choose architecture for a Flutter project, or create scalable maintainable Flutter code organization.

Why use Flutter Architecture on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MADTeacher/mad-agents-skills/tree/main/flutter-architecture. 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 Flutter Architecture?

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 Architecture?

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

Is the Flutter Architecture AI skill free?

Yes. It is published on GitHub by MADTeacher 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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