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Firebase Storage

Community
evanca
firebase-storage

Use when setting up Storage, uploading/downloading files, managing metadata, handling errors, or applying security rules.

Overview

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

Use it in TypingMind

Enable Firebase Storage 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 Storage 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 Storage 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 Storage Skill

This skill defines how to correctly use Firebase Cloud Storage in Flutter applications.

When to Use

Use this skill when:

  • Setting up Cloud Storage in a Flutter project.
  • Uploading or downloading files.
  • Managing file metadata.
  • Handling Storage errors and monitoring upload progress.

1. Setup and Configuration

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

final storage = FirebaseStorage.instance;
// Or specify a bucket explicitly:
// final storage = FirebaseStorage.instanceFor(bucket: "gs://BUCKET_NAME");
  • Firebase Storage requires the Blaze (pay-as-you-go) plan.
  • Run flutterfire configure to update your Firebase config with the default Storage bucket name.

Security note: By default, a Cloud Storage bucket requires Firebase Authentication for any action. Configuring public access may also make App Engine files publicly accessible — restrict access again when you set up Authentication.


2. File Operations

Create a reference:

dart
final storageRef = FirebaseStorage.instance.ref();
final fileRef = storageRef.child("uploads/file.jpg");

Upload:

dart
final uploadTask = fileRef.putFile(file);
final snapshot = await uploadTask;
final downloadUrl = await snapshot.ref.getDownloadURL();

Download (in-memory):

dart
final data = await fileRef.getData();

Download URL:

dart
final downloadUrl = await fileRef.getDownloadURL();

Delete:

dart
await fileRef.delete();

3. Metadata Management

Get metadata:

dart
final metadata = await fileRef.getMetadata();
print('Content type: ${metadata.contentType}');
print('Size: ${metadata.size}');

Update metadata:

dart
final newMetadata = SettableMetadata(
  contentType: "image/jpeg",
  customMetadata: {'uploaded_by': 'user123'},
);
await fileRef.updateMetadata(newMetadata);

Use custom metadata to store additional key/value pairs with your files.


4. Error Handling

Use try-catch with FirebaseException. Key error codes:

CodeMeaning
storage/object-not-foundFile doesn't exist at the reference
storage/bucket-not-foundNo bucket configured for Cloud Storage
storage/project-not-foundNo project configured for Cloud Storage
storage/quota-exceededStorage quota exceeded
storage/unauthenticatedUser needs to authenticate
storage/unauthorizedUser lacks permission
storage/retry-limit-exceededOperation timeout exceeded
  • For quota-exceeded on the Spark plan, upgrade to Blaze.
  • Implement retry logic for network-related errors and timeouts.

5. Performance and Best Practices

Monitor upload progress:

dart
final uploadTask = fileRef.putFile(file);
uploadTask.snapshotEvents.listen((TaskSnapshot snapshot) {
  print('Progress: ${(snapshot.bytesTransferred / snapshot.totalBytes) * 100}%');
});
  • Cancel uploads with uploadTask.cancel().
  • Pause / resume with uploadTask.pause() and uploadTask.resume().
  • Optimize file sizes before upload to reduce costs and improve performance.
  • Use Cloud Storage with Firestore for comprehensive data management.
  • Use the Firebase Local Emulator Suite for local development and testing.

6. Security

  • Use Firebase Security Rules to control access to files.
  • Combine Storage rules with Firebase Authentication for user-based access control.
  • Test security rules thoroughly before deploying to production.

References

Frequently asked questions

What does the Firebase Storage AI skill do?

Use when setting up Storage, uploading/downloading files, managing metadata, handling errors, or applying security rules.

Why use Firebase Storage on TypingMind?

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

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

Which AI models can use Firebase Storage?

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 Storage?

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

Is the Firebase Storage 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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