.claude/skills/flutter-expert/SKILL.md
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.
npx skillsauth add shalevamin/The-_Ultimate_agents flutter-expertInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Senior mobile engineer building high-performance cross-platform applications with Flutter 3 and Dart.
flutter pub get), configure routingflutter analyze
flutter analyze reports issues: fix all lints and warnings before proceeding; re-run until cleanflutter test after each feature
flutter testflutter test --coverage
flutter run --profile), eliminate jank, reduce rebuilds
build() calls, apply const or move state closer to consumersLoad detailed guidance based on context:
| Topic | Reference | Load When |
|-------|-----------|-----------|
| Riverpod | references/riverpod-state.md | State management, providers, notifiers |
| Bloc | references/bloc-state.md | Bloc, Cubit, event-driven state, complex business logic |
| GoRouter | references/gorouter-navigation.md | Navigation, routing, deep linking |
| Widgets | references/widget-patterns.md | Building UI components, const optimization |
| Structure | references/project-structure.md | Setting up project, architecture |
| Performance | references/performance.md | Optimization, profiling, jank fixes |
// 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});
@override
Widget build(BuildContext context, WidgetRef ref) {
final count = ref.watch(counterProvider);
return Text('$count');
}
}
// ❌ 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});
@override
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
);
}
}
const constructors wherever possibleConsumer/ConsumerWidget for state (not StatefulWidget)flutter_testbuild() methodsetState for app-wide stateconst on static widgetscompute())| Symptom | Likely Cause | Recovery |
|---------|-------------|----------|
| flutter analyze errors | Unresolved imports, missing const, type mismatches | Fix flagged lines; run flutter pub get if imports are missing |
| Widget test assertion failures | Widget tree mismatch or async state not settled | Use tester.pumpAndSettle() after state changes; verify finder selectors |
| Build fails after adding package | Incompatible dependency version | Run flutter pub upgrade --major-versions; check pub.dev compatibility |
| Jank / dropped frames | Expensive build() calls, uncached widgets, heavy main-thread work | Use RepaintBoundary, move heavy work to compute(), add const |
| Hot reload not reflecting changes | State held in StateNotifier not reset | Use hot restart (R in terminal) to reset full app state |
When implementing Flutter features, provide:
const usagetesting
Use when fine-tuning LLMs, training custom models, or adapting foundation models for specific tasks. Invoke for configuring LoRA/QLoRA adapters, preparing JSONL training datasets, setting hyperparameters for fine-tuning runs, adapter training, transfer learning, finetuning with Hugging Face PEFT, OpenAI fine-tuning, instruction tuning, RLHF, DPO, or quantizing and deploying fine-tuned models. Trigger terms include: LoRA, QLoRA, PEFT, finetuning, fine-tuning, adapter tuning, LLM training, model training, custom model.
tools
Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.
tools
Translate Figma nodes into production-ready code with 1:1 visual fidelity using the Figma MCP workflow (design context, screenshots, assets, and project-convention translation). Trigger when the user provides Figma URLs or node IDs, or asks to implement designs or components that must match Figma specs. Requires a working Figma MCP server connection.
development
Conducts structured requirements workshops to produce feature specifications, user stories, EARS-format functional requirements, acceptance criteria, and implementation checklists. Use when defining new features, gathering requirements, or writing specifications. Invoke for feature definition, requirements gathering, user stories, EARS format specs, PRDs, acceptance criteria, or requirement matrices.