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Firebase Data Connect

Community
evanca
firebase-data-connect

Use when setting up Data Connect, writing GraphQL queries/mutations, configuring generated SDKs, handling offline, or applying security rules.

Overview

Publisherevanca
Repositoryflutter-ai-rules
Skill namefirebase-data-connect
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 Firebase Data Connect 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/firebase-data-connect
  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/firebase-data-connect .claude/skills/firebase-data-connect
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Firebase Data Connect 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 Firebase Data Connect 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 Firebase Data Connect 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.

Firebase Data Connect Skill

This skill defines how to correctly use Firebase Data Connect in Flutter applications.

When to Use

Use this skill when:

  • Setting up and configuring Firebase Data Connect in a Flutter project.
  • Designing schemas, queries, and mutations for Data Connect.
  • Implementing generated SDK calls for typed queries and mutations.
  • Handling network failures, data inconsistencies, and offline scenarios.
  • Applying security and performance best practices.

1. Setup and Configuration

Step 1: Install the package

flutter pub add firebase_data_connect

Step 2: Import and initialize

dart
import 'package:firebase_data_connect/firebase_data_connect.dart';
import 'package:firebase_core/firebase_core.dart';
import 'firebase_options.dart';

await Firebase.initializeApp(
  options: DefaultFirebaseOptions.currentPlatform,
);

Step 3: Define a schema in dataconnect/schema/schema.gql

graphql
type Movie @table {
  id: UUID! @default(expr: "uuidV4()")
  title: String!
  releaseYear: Int
  genre: String
  rating: Float
  description: String
}

Step 4: Define queries and mutations in dataconnect/connector/queries.gql

graphql
query ListMovies @auth(level: PUBLIC) {
  movies {
    id
    title
    releaseYear
    genre
    rating
  }
}

mutation CreateMovie($title: String!, $releaseYear: Int, $genre: String) @auth(level: USER) {
  movie_insert(data: {
    title: $title
    releaseYear: $releaseYear
    genre: $genre
  })
}

mutation DeleteMovie($id: UUID!) @auth(level: USER) {
  movie_delete(id: $id)
}

Step 5: Generate the typed Flutter SDK

flutterfire generate

This produces typed Dart classes for each query and mutation.

Platform support:

PlatformSupport
iOSFull
AndroidFull
WebFull
Other platformsNot supported

2. Executing Queries and Mutations

Use the generated SDK to execute typed queries and mutations:

dart
// Execute a query
final result = await ListMoviesQuery().execute();
final movies = result.data.movies;

// Execute a mutation
await CreateMovieMutation(title: 'Inception', releaseYear: 2010, genre: 'Sci-Fi')
    .execute();

// Delete by ID
await DeleteMovieMutation(id: movieId).execute();

Real-Time Listeners

Subscribe to query changes for live updates:

dart
final subscription = ListMoviesQuery().subscribe();
subscription.listen((result) {
  final movies = result.data.movies;
  // Update UI with latest movie list
});

3. Performance and Caching

  • Design efficient queries requesting only the fields needed to minimize data transfer.
  • Implement pagination for large datasets:
    graphql
    query ListMoviesPaginated($limit: Int!, $offset: Int!) @auth(level: PUBLIC) {
      movies(limit: $limit, offset: $offset) {
        id
        title
        releaseYear
      }
    }
  • Use real-time listeners judiciously to avoid unnecessary network usage.
  • Consider offline capabilities for critical app functionality by caching query results locally.

4. Error Handling

Wrap Data Connect calls in try/catch to handle network and validation errors:

dart
try {
  final result = await ListMoviesQuery().execute();
  return result.data.movies;
} on FirebaseException catch (e) {
  if (e.code == 'unavailable') {
    // Handle offline — return cached data
    return _localCache.getMovies();
  }
  rethrow;
}
  • Implement retry logic with exponential backoff for transient connection errors.
  • Provide meaningful error messages for data validation failures.
  • Monitor error rates and investigate recurring issues.

5. Security

  • Use @auth directives in schema to control access levels (PUBLIC, USER, NO_ACCESS).
  • Integrate Firebase Authentication for user-based access control.
  • Validate data on both client and server sides.
  • Follow data privacy best practices when handling user information.

References

Frequently asked questions

What does the Firebase Data Connect AI skill do?

Use when setting up Data Connect, writing GraphQL queries/mutations, configuring generated SDKs, handling offline, or applying security rules.

Why use Firebase Data Connect on TypingMind?

Because you install it once and use it with any model. Firebase Data Connect 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 Firebase Data Connect in TypingMind?

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

Which AI models can use Firebase Data Connect?

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 Firebase Data Connect?

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

Is the Firebase Data Connect 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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