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Flutter App Architecture with Clean Architecture

Scaffold a Flutter app with clean architecture: BLoC/Riverpod, repository pattern, dependency injection, and feature-first structure.

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What this prompt does

This prompt scaffolds a Flutter application for [app_purpose] using clean architecture. It lays out a feature-first folder structure for your [features], state management with [state_management], the repository pattern over [data_sources], dependency injection via [di_package], navigation with [router_package], Either-based error handling (dartz), local storage with [local_storage], a Dio API client with interceptors, retry, and token refresh, a theme system with [theme_count] themes, and unit plus widget tests. It also asks for an app-initialization flow, environment configuration for dev/staging/prod, and CI/CD with [ci_platform].

The structure works because clean architecture separates domain, data, and presentation so adding a feature stays additive instead of forcing a rewrite. A feature-first layout keeps each capability in its own slice, the repository pattern isolates [data_sources] behind interfaces, and [di_package] wires it together so layers stay swappable and testable. Either-based error handling means failures flow as values, so the app degrades gracefully rather than crashing on an unhandled exception.

When to use it

  • You're starting a new Flutter app and want a maintainable structure before features pile on.
  • You expect the app to grow and need domain, data, and presentation cleanly separated.
  • You want a tested Dio API client with token refresh and retry from day one.
  • You need environment configuration for dev, staging, and production baked in.
  • You're standardizing how your team structures Flutter projects.
  • You want light and dark theming and CI/CD set up alongside the architecture.

Example output

Expect a project skeleton: a feature-first directory tree for your [features], repository and data-source interfaces, DI registration with [di_package], route definitions in [router_package], a Dio client with interceptors, Either-returning use cases, and example unit and widget tests. The environment configuration and a [ci_platform] pipeline round it out so the app builds and tests from a clean checkout.

Pro tips

  • Name your real [features] so the generated folders match your app; generic feature names leave you renaming everything afterward.
  • Pick [state_management] your team knows — flutter_bloc and Riverpod both fit clean architecture, but consistency matters more than the choice.
  • Be explicit about [data_sources] (REST plus an SQLite cache, for example) so the repository layer models online and offline paths correctly.
  • Keep [di_package] as get_it plus injectable if you want code-generated registration; it scales better than wiring dependencies by hand.
  • Set [local_storage] per data type — lightweight key-value for settings, a relational store for structured data — rather than forcing one tool to do both.
  • Treat the generated tests as a starting harness and expand coverage on the domain layer first, since that's where business rules live.

Frequently Asked Questions

Which state management does this prompt use?
Whatever you set for `[state_management]` — flutter_bloc by default, but Riverpod works equally well. Clean architecture doesn't depend on the choice, so the repository and domain layers stay identical regardless of which you specify.
Why does it use Either for error handling?
Either from dartz returns failures as values instead of throwing, so every call site must handle both success and error paths. That makes the app degrade gracefully under network or data failures rather than crashing on an unhandled exception.
Does the generated API client handle token refresh?
Yes. It builds a Dio client with interceptors, retry logic, and token refresh, so expired tokens are renewed transparently and failed requests retry without you wiring that plumbing into every call manually.
Can I use a different DI package than the default?
Yes. Set `[di_package]` to your preference. The default of get_it with injectable gives you code-generated registration that scales well, but any DI approach fits as long as it keeps the layers loosely coupled.
Is this overkill for a small app?
For a quick prototype, the full clean-architecture layering can be more structure than you need. It pays off when the app is expected to grow, because the separation between domain, data, and presentation keeps later features additive.
Engr Mejba Ahmed

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Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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