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Firebase Cloud Functions

Community
evanca
firebase-cloud-functions

Use when calling callable functions (httpsCallable), passing data to server-side logic, handling function errors/timeouts, configuring regions, or testing with the Emulator Suite.

Overview

Publisherevanca
Repositoryflutter-ai-rules
Skill namefirebase-cloud-functions
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 Cloud Functions 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-cloud-functions
  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-cloud-functions .claude/skills/firebase-cloud-functions
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Firebase Cloud Functions 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 Cloud Functions 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 Cloud Functions 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 Cloud Functions Skill

This skill defines how to correctly call Firebase Cloud Functions from Flutter applications.

When to Use

Use this skill when:

  • Implementing callable Cloud Functions in a Flutter project.
  • Passing structured data to server-side functions and processing results.
  • Handling errors, timeouts, and retries for function calls.
  • Configuring region-specific function deployments.
  • Testing Cloud Functions locally with the Firebase Emulator Suite.

1. Setup and Configuration

flutter pub add cloud_functions
dart
import 'package:cloud_functions/cloud_functions.dart';

// After Firebase.initializeApp():
final functions = FirebaseFunctions.instance;
  • Initialize Firebase before using any Cloud Functions features.
  • For region-specific deployments, specify the region:
dart
final functions = FirebaseFunctions.instanceFor(region: 'europe-west1');
  • Deploy callable functions to Firebase before attempting to call them from the Flutter app.
  • Consider implementing App Check to prevent abuse of Cloud Functions.

2. Calling Functions

Use httpsCallable to reference a function, then call to invoke it:

dart
final result = await FirebaseFunctions.instance
  .httpsCallable('functionName')
  .call(data);
  • Pass data as a Map — it is automatically serialized to JSON:
dart
final result = await FirebaseFunctions.instance
  .httpsCallable('addMessage')
  .call({
    "text": messageText,
    "push": true,
  });
  • Access the result via the data property — it is automatically deserialized from JSON:
dart
final responseData = result.data;
// Cast to expected type if needed:
final message = result.data as Map<String, dynamic>;
final status = message['status'] as String;
  • Do not pass authentication tokens in function parameters — they are automatically included by the SDK.
  • Keep function names consistent between client code and server-side implementations.

3. Error Handling

Always wrap function calls in try-catch and check for FirebaseFunctionsException:

dart
try {
  final result = await FirebaseFunctions.instance
    .httpsCallable('functionName')
    .call(data);
  // Handle successful result
} on FirebaseFunctionsException catch (e) {
  switch (e.code) {
    case 'not-found':
      // Function does not exist
      break;
    case 'permission-denied':
      // User lacks permission
      break;
    case 'unavailable':
      // Service temporarily unavailable — retry
      break;
    default:
      debugPrint('Function error [${e.code}]: ${e.message}');
  }
} catch (e) {
  debugPrint('Unexpected error: $e');
}
  • Handle network connectivity issues and timeouts appropriately.
  • Provide meaningful error messages to users when function calls fail.
  • Implement retry logic with exponential backoff for transient errors (unavailable, deadline-exceeded).

4. Performance Optimization

Set a timeout appropriate to the expected execution time:

dart
final callable = FirebaseFunctions.instance.httpsCallable(
  'functionName',
  options: HttpsCallableOptions(
    timeout: const Duration(seconds: 30),
  ),
);
  • Minimize the amount of data passed to and from functions to reduce latency.
  • Use batch operations when possible to reduce the number of function calls.
  • Consider client-side caching for frequently used function results.
  • Account for cold starts for infrequently used functions.
  • Implement proper loading states in the UI while waiting for function responses.

5. Testing and Development

Use the Firebase Emulator Suite for local development and testing:

dart
FirebaseFunctions.instance.useFunctionsEmulator('localhost', 5001);
  • Test functions with both valid and invalid inputs to ensure proper validation.
  • Verify that functions handle authentication correctly.
  • Test with different user roles and permissions to ensure proper access control.
  • Implement unit tests for client-side function calling logic.

References

Frequently asked questions

What does the Firebase Cloud Functions AI skill do?

Use when calling callable functions (httpsCallable), passing data to server-side logic, handling function errors/timeouts, configuring regions, or testing with the Emulator Suite.

Why use Firebase Cloud Functions on TypingMind?

Because you install it once and use it with any model. Firebase Cloud Functions 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 Cloud Functions in TypingMind?

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

Which AI models can use Firebase Cloud Functions?

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 Cloud Functions?

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

Is the Firebase Cloud Functions 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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