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Firebase Cloud Firestore

Community
evanca
firebase-cloud-firestore

Use when setting up Firestore, designing schemas, doing CRUD, creating listeners, paginating queries, configuring indexes, enabling offline persistence, or writing security rules.

Overview

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

Use it in TypingMind

Enable Firebase Cloud Firestore 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 Firestore 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 Firestore 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 Firestore Skill

This skill defines how to correctly implement Cloud Firestore in Flutter applications, covering data modeling, queries, real-time updates, security rules, and scale optimization.

When to Use

Use this skill when:

  • Setting up and configuring Cloud Firestore in a Flutter project.
  • Designing document and collection structure or planning subcollections.
  • Performing read, write, batch, or transaction operations.
  • Implementing real-time listeners or paginated queries.
  • Optimizing for scale and avoiding write hotspots.
  • Writing or debugging Firestore security rules.

1. Database Selection

Choose Cloud Firestore when the app needs:

  • Rich, hierarchical data models with subcollections.
  • Complex queries: chaining filters, combining filtering and sorting on a property.
  • Transactions that atomically read and write data from any part of the database.
  • High availability (typical uptime 99.999%) or critical-level reliability.
  • Automatic scaling to millions of concurrent users.

Use Realtime Database instead for simple data models requiring simple lookups and extremely low-latency synchronization (typical response times under 10ms).


2. Setup and Configuration

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

final db = FirebaseFirestore.instance; // after Firebase.initializeApp()

Location:

  • Select the database location closest to users and compute resources.
  • Use multi-region locations for critical apps (maximum availability and durability).
  • Use regional locations for lower costs and lower write latency.

iOS/macOS: Consider pre-compiled frameworks to improve build times:

ruby
pod 'FirebaseFirestore',
  :git => 'https://github.com/invertase/firestore-ios-sdk-frameworks.git',
  :tag => 'IOS_SDK_VERSION'

Offline persistence is enabled by default on mobile. Configure cache size:

dart
FirebaseFirestore.instance.settings = const Settings(
  persistenceEnabled: true,
  cacheSizeBytes: Settings.CACHE_SIZE_UNLIMITED,
);

3. Document Structure

  • Avoid document IDs . and .. (special meaning in Firestore paths).
  • Avoid forward slashes (/) in document IDs (path separators).
  • Do not use monotonically increasing document IDs (e.g., Customer1, Customer2) — causes write hotspots.
  • Use Firestore's automatic document IDs when possible:
dart
final docRef = await db.collection("users").add({
  'name': 'Ada Lovelace',
  'email': 'ada@example.com',
  'created_at': FieldValue.serverTimestamp(),
});
print('Created document with ID: ${docRef.id}');
  • Avoid these characters in field names (require extra escaping): . [ ] * `
  • Use subcollections within documents to organize complex, hierarchical data rather than deeply nested objects.

4. Indexing

  • Firestore queries are indexed by default; query performance is proportional to the result set size, not the dataset size.
  • Set collection-level index exemptions to reduce write latency and storage costs.
  • Disable Descending and Array indexing for fields that do not need them.
  • Exempt string fields with long values that are not used for querying.
  • Exempt fields with sequential values (e.g., timestamps) from indexing if not used in queries — avoids the 500 writes/second index limit.
  • Add single-field exemptions for TTL fields.
  • Exempt large array or map fields not used in queries — avoids the 40,000 index entries per document limit.

5. Read and Write Operations

Read All Documents in a Collection

dart
final querySnapshot = await db.collection("users").get();
for (var doc in querySnapshot.docs) {
  print("${doc.id} => ${doc.data()}");
}

Query with Filters

dart
final query = db.collection("users")
    .where("age", isGreaterThanOrEqualTo: 18)
    .orderBy("age")
    .limit(20);

final results = await query.get();

Cursor-Based Pagination

dart
// First page
final first = db.collection("cities").orderBy("name").limit(25);
final firstSnapshot = await first.get();

// Next page using last document as cursor
final lastDoc = firstSnapshot.docs.last;
final next = db.collection("cities")
    .orderBy("name")
    .startAfterDocument(lastDoc)
    .limit(25);
  • Do not use offsets for pagination — use cursors to avoid retrieving and being billed for skipped documents.

Write with Server Timestamp

dart
await db.collection("users").doc("user_1").set({
  'name': 'Grace Hopper',
  'updated_at': FieldValue.serverTimestamp(),
});

Batch Write (Atomic, Up to 500 Operations)

dart
final batch = db.batch();
batch.set(db.collection("cities").doc("LA"), {'name': 'Los Angeles'});
batch.update(db.collection("cities").doc("SF"), {'population': 860000});
batch.delete(db.collection("cities").doc("OLD"));
await batch.commit();

Transaction

dart
await db.runTransaction((transaction) async {
  final snapshot = await transaction.get(db.collection("counters").doc("visits"));
  final currentCount = snapshot.get("count") as int;
  transaction.update(snapshot.reference, {"count": currentCount + 1});
});
  • Execute independent operations (e.g., a document lookup and a query) in parallel, not sequentially.
  • Be aware of write rate limits: ~1 write per second per document.
  • For writing a large number of documents, use a bulk writer instead of the atomic batch writer.

6. Designing for Scale

  • Avoid high read or write rates to lexicographically close documents (hotspotting).
  • Avoid creating new documents with monotonically increasing fields (like timestamps) at a very high rate.
  • Avoid deleting documents in a collection at a high rate.
  • Gradually increase traffic when writing to the database at a high rate — ramp up over 5 minutes.
  • Avoid queries that skip over recently deleted data — use start_at to find the correct start point.
  • Distribute writes across different document paths to avoid contention.
  • Firestore scales automatically to ~1 million concurrent connections and 10,000 writes/second.

7. Real-time Updates

dart
final subscription = db.collection("messages")
    .where("room", isEqualTo: "general")
    .orderBy("timestamp", descending: true)
    .limit(50)
    .snapshots()
    .listen((querySnapshot) {
      for (var change in querySnapshot.docChanges) {
        switch (change.type) {
          case DocumentChangeType.added:
            print("New message: ${change.doc.data()}");
            break;
          case DocumentChangeType.modified:
            print("Modified: ${change.doc.data()}");
            break;
          case DocumentChangeType.removed:
            print("Removed: ${change.doc.id}");
            break;
        }
      }
    });

// Detach when no longer needed:
subscription.cancel();
  • Limit the number of simultaneous real-time listeners.
  • Detach listeners when they are no longer needed to avoid memory leaks and unnecessary reads.
  • Use compound queries to filter data server-side rather than filtering on the client.
  • For large collections, use queries to limit the data being listened to — never listen to an entire large collection.

8. Security

  • Always use Firebase Security Rules to protect Firestore data.
  • Security rules do not cascade unless a wildcard is used.
  • If a query's results might contain data the user does not have access to, the entire query fails.

Example rules for user-owned documents:

rules_version = '2';
service cloud.firestore {
  match /databases/{database}/documents {
    match /users/{userId} {
      allow read, update, delete: if request.auth != null && request.auth.uid == userId;
      allow create: if request.auth != null;
    }
  }
}
  • Validate user input before submitting to Firestore to prevent injection attacks.
  • Use transactions for operations that require atomic updates to multiple documents.
  • Implement proper error handling for all Firestore operations.
  • Never store sensitive information in Firestore without proper access controls.

References

Frequently asked questions

What does the Firebase Cloud Firestore AI skill do?

Use when setting up Firestore, designing schemas, doing CRUD, creating listeners, paginating queries, configuring indexes, enabling offline persistence, or writing security rules.

Why use Firebase Cloud Firestore on TypingMind?

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

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

Which AI models can use Firebase Cloud Firestore?

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 Firestore?

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

Is the Firebase Cloud Firestore 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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