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Effective Dart

Community
evanca
effective-dart

Use when writing Dart code, reviewing for style, refactoring naming, adding doc comments, structuring imports, or enforcing type annotations.

Overview

Publisherevanca
Repositoryflutter-ai-rules
Skill nameeffective-dart
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 Effective Dart 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/effective-dart
  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/effective-dart .claude/skills/effective-dart
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Effective Dart 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 Effective Dart 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 Effective Dart 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.

Effective Dart Skill

This skill defines how to write idiomatic, high-quality Dart and Flutter code following Effective Dart guidelines.


1. Naming Conventions

KindConventionExample
Classes, enums, typedefs, type parameters, extensionsUpperCamelCaseMyWidget, UserState
Packages, directories, source fileslowercase_with_underscoresuser_profile.dart
Import prefixeslowercase_with_underscoresimport '...' as my_prefix;
Variables, parameters, named parameters, functionslowerCamelCaseuserName, fetchData()
  • Capitalize acronyms and abbreviations longer than two letters like words: HttpRequest, not HTTPRequest.
  • Avoid abbreviations unless the abbreviation is more common than the full term.
  • Prefer putting the most descriptive noun last in names.
  • Use terms consistently throughout your code.
  • Follow mnemonic conventions for type parameters: E (element), K/V (key/value), T/S/U (generic types).
  • Consider making code read like a sentence when designing APIs.
  • Prefer a noun phrase for non-boolean properties or variables.
  • Prefer a non-imperative verb phrase for boolean properties or variables; prefer the positive form.
  • Consider omitting the verb for named boolean parameters.
  • Avoid starting a function or method name with get; prefer removing get and using a getter when the API conceptually exposes a property.

2. Types and Functions

  • Use class modifiers (final, sealed, interface, base, mixin) to control whether a class can be extended or implemented.
  • Type annotate variables without initializers.
  • Type annotate fields and top-level variables if the type isn't obvious.
  • Annotate return types on function declarations.
  • Annotate parameter types on function declarations.
  • Write type arguments on generic invocations that aren't inferred.
  • Annotate with dynamic instead of letting inference fail.
  • Use Future<void> as the return type of async members that do not produce values.
  • Use getters for operations that conceptually access properties.
  • Use setters for operations that conceptually change properties.
  • Use a function declaration to bind a function to a name.
  • Use inclusive start and exclusive end parameters to accept a range.
dart
// Prefer: explicit class modifier
final class AppConfig {
  final String apiUrl;
  final int timeout;
  const AppConfig({required this.apiUrl, required this.timeout});
}

// Prefer: sealed for exhaustive pattern matching
sealed class Result<T> {}
class Success<T> extends Result<T> { final T value; Success(this.value); }
class Failure<T> extends Result<T> { final Exception error; Failure(this.error); }

3. Style

bash
dart format .
  • Format code with dart format — don't manually format.
  • Use curly braces for all flow control statements.
  • Prefer final over var when variable values won't change.
  • Use const for compile-time constants.
  • Prefer lines 80 characters or fewer for readability.

4. Imports and Files

  • Don't import libraries inside the src directory of another package.
  • Don't allow import paths to reach into or out of lib.
  • Prefer relative import paths within a package.
  • Don't use /lib/ or ../ in import paths.
  • Consider writing a library-level doc comment for library files.

5. Structure

  • Keep files focused on a single responsibility.
  • Limit file length to maintain readability.
  • Group related functionality together.
  • Prefer making fields and top-level variables final.
  • Consider making constructors const if the class supports it.
  • Prefer making declarations private — only expose what's necessary.

6. Usage Patterns

dart
// Adjacent string concatenation (not +)
final greeting = 'Hello, '
    'world!';

// Collection literals
final list = [1, 2, 3];
final map = {'key': 'value'};

// Initializing formals
class Point {
  final double x, y;
  Point(this.x, this.y);
}

// Empty constructor body
class Empty {
  Empty();  // not Empty() {}
}

// rethrow to preserve stack trace
try {
  doSomething();
} catch (e) {
  log(e);
  rethrow;
}
  • Use whereType<T>() to filter a collection by type.
  • Follow a consistent rule for var and final on local variables.
  • Initialize fields at their declaration when possible.
  • Override hashCode if you override ==; ensure == obeys mathematical equality rules.
  • Prefer specific exception handling: use on SomeException catch (e) instead of broad catch (e) or .catchError handlers.

7. Documentation

dart
/// Returns the sum of [a] and [b].
///
/// Throws [ArgumentError] if either value is negative.
int add(int a, int b) { ... }
  • Format comments like sentences (capitalize, end with period).
  • Use /// doc comments — not /* */ block comments — for types and members.
  • Prefer writing doc comments for public APIs; consider them for private APIs too.
  • Start doc comments with a single-sentence summary, separated into its own paragraph.
  • Avoid redundancy with the surrounding context.
  • Start function/method comments with a third-person verb if the main purpose is a side effect.
  • Start with a noun or non-imperative verb phrase if returning a value is the primary purpose.
  • Start boolean variable/property comments with "Whether" followed by a noun or gerund phrase.
  • Use [identifier] in doc comments to refer to in-scope identifiers.
  • Use prose to explain parameters, return values, and exceptions (e.g., "The [param]", "Returns", "Throws" sections).
  • Put doc comments before metadata annotations.
  • Document why code exists or how it should be used, not just what it does.

8. Testing Patterns

  • Write unit tests for business logic, using group and descriptive test names:
dart
import 'package:test/test.dart';

void main() {
  group('CartService', () {
    late CartService cart;

    setUp(() => cart = CartService());

    test('addItem increases item count', () {
      cart.addItem(Product(id: '1', name: 'Widget', price: 9.99));
      expect(cart.items, hasLength(1));
    });

    test('removeItem decreases total price', () {
      final product = Product(id: '1', name: 'Widget', price: 9.99);
      cart.addItem(product);
      cart.removeItem(product.id);
      expect(cart.totalPrice, equals(0.0));
    });
  });
}
  • Write widget tests using testWidgets and WidgetTester:
dart
import 'package:flutter_test/flutter_test.dart';

void main() {
  testWidgets('LoginButton shows loading indicator when tapped',
      (WidgetTester tester) async {
    await tester.pumpWidget(const MaterialApp(home: LoginScreen()));
    await tester.tap(find.byType(ElevatedButton));
    await tester.pump();
    expect(find.byType(CircularProgressIndicator), findsOneWidget);
  });
}

9. Code Review Workflow

When reviewing Dart code for Effective Dart compliance, the agent should check:

  1. Naming — verify all identifiers follow the conventions in Section 1.
  2. Type annotations — confirm public API parameters, return types, and uninitialized variables are annotated.
  3. Class modifiers — verify final, sealed, or interface is used where appropriate.
  4. Documentation — confirm all public members have /// doc comments with a single-sentence summary.
  5. Style — run dart format --output=none --set-exit-if-changed . to verify formatting.
  6. Analysis — run dart analyze and confirm zero issues.

References

Frequently asked questions

What does the Effective Dart AI skill do?

Use when writing Dart code, reviewing for style, refactoring naming, adding doc comments, structuring imports, or enforcing type annotations.

Why use Effective Dart on TypingMind?

Because you install it once and use it with any model. Effective Dart 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 Effective Dart in TypingMind?

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

Which AI models can use Effective Dart?

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 Effective Dart?

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

Is the Effective Dart 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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