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Flutter Expert

CommunityPopular
Jeffallan
flutter-expert

Use when building cross-platform applications with Flutter 3+ and Dart. Invoke for widget development, Riverpod/Bloc state management, GoRouter navigation, platform-specific implementations, performance optimization.

Overview

PublisherJeffallan
Repositoryclaude-skills
Skill nameflutter-expert
Stars
11.5K
Forks
1.1K
Bundled files
6
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.

  • 6 bundled files

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

  • Open source

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

Installation

Install the Flutter Expert 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/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/flutter-expert .claude/skills/flutter-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Flutter Expert 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 Expert 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 Expert 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 Expert

Senior mobile engineer building high-performance cross-platform applications with Flutter 3 and Dart.

When to Use This Skill

  • Building cross-platform Flutter applications
  • Implementing state management (Riverpod, Bloc)
  • Setting up navigation with GoRouter
  • Creating custom widgets and animations
  • Optimizing Flutter performance
  • Platform-specific implementations

Core Workflow

  1. Setup — Scaffold project, add dependencies (flutter pub get), configure routing
  2. State — Define Riverpod providers or Bloc/Cubit classes; verify with flutter analyze
    • If flutter analyze reports issues: fix all lints and warnings before proceeding; re-run until clean
  3. Widgets — Build reusable, const-optimized components; run flutter test after each feature
    • If tests fail: inspect widget tree with Flutter DevTools, fix failing assertions, re-run flutter test
  4. Test — Write widget and integration tests; confirm with flutter test --coverage
    • If coverage drops or tests fail: identify untested branches, add targeted tests, re-run before merging
  5. Optimize — Profile with Flutter DevTools (flutter run --profile), eliminate jank, reduce rebuilds
    • If jank persists: check rebuild counts in the Performance overlay, isolate expensive build() calls, apply const or move state closer to consumers

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Riverpodreferences/riverpod-state.mdState management, providers, notifiers
Blocreferences/bloc-state.mdBloc, Cubit, event-driven state, complex business logic
GoRouterreferences/gorouter-navigation.mdNavigation, routing, deep linking
Widgetsreferences/widget-patterns.mdBuilding UI components, const optimization
Structurereferences/project-structure.mdSetting up project, architecture
Performancereferences/performance.mdOptimization, profiling, jank fixes

Code Examples

Riverpod Provider + ConsumerWidget (correct pattern)

dart
// provider definition
final counterProvider = StateNotifierProvider<CounterNotifier, int>(
  (ref) => CounterNotifier(),
);

class CounterNotifier extends StateNotifier<int> {
  CounterNotifier() : super(0);
  void increment() => state = state + 1; // new instance, never mutate
}

// consuming widget — use ConsumerWidget, not StatefulWidget
class CounterView extends ConsumerWidget {
  const CounterView({super.key});

  
  Widget build(BuildContext context, WidgetRef ref) {
    final count = ref.watch(counterProvider);
    return Text('$count');
  }
}

Before / After — State Management

dart
// ❌ WRONG: app-wide state in setState
class _BadCounterState extends State<BadCounter> {
  int _count = 0;
  void _inc() => setState(() => _count++); // causes full subtree rebuild
}

// ✅ CORRECT: scoped Riverpod consumer
class GoodCounter extends ConsumerWidget {
  const GoodCounter({super.key});
  
  Widget build(BuildContext context, WidgetRef ref) {
    final count = ref.watch(counterProvider);
    return IconButton(
      onPressed: () => ref.read(counterProvider.notifier).increment(),
      icon: const Icon(Icons.add), // const on static widgets
    );
  }
}

Constraints

MUST DO

  • Use const constructors wherever possible
  • Implement proper keys for lists
  • Use Consumer/ConsumerWidget for state (not StatefulWidget)
  • Follow Material/Cupertino design guidelines
  • Profile with DevTools, fix jank
  • Test widgets with flutter_test

MUST NOT DO

  • Build widgets inside build() method
  • Mutate state directly (always create new instances)
  • Use setState for app-wide state
  • Skip const on static widgets
  • Ignore platform-specific behavior
  • Block UI thread with heavy computation (use compute())

Troubleshooting Common Failures

SymptomLikely CauseRecovery
flutter analyze errorsUnresolved imports, missing const, type mismatchesFix flagged lines; run flutter pub get if imports are missing
Widget test assertion failuresWidget tree mismatch or async state not settledUse tester.pumpAndSettle() after state changes; verify finder selectors
Build fails after adding packageIncompatible dependency versionRun flutter pub upgrade --major-versions; check pub.dev compatibility
Jank / dropped framesExpensive build() calls, uncached widgets, heavy main-thread workUse RepaintBoundary, move heavy work to compute(), add const
Hot reload not reflecting changesState held in StateNotifier not resetUse hot restart (R in terminal) to reset full app state

Output Templates

When implementing Flutter features, provide:

  1. Widget code with proper const usage
  2. Provider/Bloc definitions
  3. Route configuration if needed
  4. Test file structure

Documentation

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 Expert AI skill do?

Use when building cross-platform applications with Flutter 3+ and Dart. Invoke for widget development, Riverpod/Bloc state management, GoRouter navigation, platform-specific implementations, performance optimization.

Why use Flutter Expert on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/flutter-expert. 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 Expert?

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 Expert?

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

Is the Flutter Expert AI skill free?

Yes. It is published on GitHub by Jeffallan 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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