GCP Firestore
Cloud Firestore is a flexible, scalable NoSQL document database. It supports real-time synchronization, offline access, and scales automatically. Available in Native mode (real-time + offline) and Datastore mode (server-only, higher throughput).
Best use case
GCP Firestore is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Cloud Firestore is a flexible, scalable NoSQL document database. It supports real-time synchronization, offline access, and scales automatically. Available in Native mode (real-time + offline) and Datastore mode (server-only, higher throughput).
Teams using GCP Firestore should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/gcp-firestore/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How GCP Firestore Compares
| Feature / Agent | GCP Firestore | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Cloud Firestore is a flexible, scalable NoSQL document database. It supports real-time synchronization, offline access, and scales automatically. Available in Native mode (real-time + offline) and Datastore mode (server-only, higher throughput).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# GCP Firestore
Cloud Firestore is a flexible, scalable NoSQL document database. It supports real-time synchronization, offline access, and scales automatically. Available in Native mode (real-time + offline) and Datastore mode (server-only, higher throughput).
## Core Concepts
- **Document** — a record containing fields (like a JSON object), identified by ID
- **Collection** — a group of documents
- **Subcollection** — a collection nested under a document
- **Reference** — a pointer to a document or collection location
- **Real-time listener** — streams live changes to documents or queries
- **Security Rules** — declarative access control for client SDKs
## CRUD Operations
```python
# Initialize and write documents
from google.cloud import firestore
db = firestore.Client()
# Create or overwrite a document
db.collection('users').document('user-001').set({
'name': 'Alice Johnson',
'email': 'alice@example.com',
'role': 'admin',
'created_at': firestore.SERVER_TIMESTAMP
})
# Add a document with auto-generated ID
ref = db.collection('orders').add({
'user_id': 'user-001',
'items': [
{'name': 'Widget', 'qty': 2, 'price': 29.99},
{'name': 'Gadget', 'qty': 1, 'price': 49.99}
],
'total': 109.97,
'status': 'pending',
'created_at': firestore.SERVER_TIMESTAMP
})
print(f"Created order: {ref[1].id}")
```
```python
# Read a document
doc = db.collection('users').document('user-001').get()
if doc.exists:
print(f"User: {doc.to_dict()}")
```
```python
# Update specific fields (merge)
db.collection('users').document('user-001').update({
'role': 'superadmin',
'updated_at': firestore.SERVER_TIMESTAMP
})
# Update nested fields
db.collection('users').document('user-001').update({
'preferences.theme': 'dark',
'preferences.notifications': True
})
```
```python
# Delete a document
db.collection('users').document('user-001').delete()
# Delete a specific field
db.collection('users').document('user-001').update({
'temporary_field': firestore.DELETE_FIELD
})
```
## Queries
```python
# Simple queries
users_ref = db.collection('users')
# Filter by field
admins = users_ref.where('role', '==', 'admin').stream()
# Multiple conditions
recent_orders = db.collection('orders') \
.where('status', '==', 'pending') \
.where('total', '>=', 50) \
.order_by('total', direction=firestore.Query.DESCENDING) \
.limit(20) \
.stream()
for order in recent_orders:
print(f"{order.id}: ${order.to_dict()['total']}")
```
```python
# Pagination with cursors
first_page = db.collection('orders') \
.order_by('created_at', direction=firestore.Query.DESCENDING) \
.limit(25) \
.get()
# Get next page starting after last document
last_doc = first_page[-1]
next_page = db.collection('orders') \
.order_by('created_at', direction=firestore.Query.DESCENDING) \
.start_after(last_doc) \
.limit(25) \
.get()
```
```python
# Array and IN queries
# Find users with a specific tag
db.collection('users').where('tags', 'array_contains', 'premium').stream()
# Find orders with specific statuses
db.collection('orders').where('status', 'in', ['pending', 'processing']).stream()
```
## Real-Time Listeners
```javascript
// real-time-listener.js — listen for live document changes
const { Firestore } = require('@google-cloud/firestore');
const db = new Firestore();
// Listen to a single document
const unsubscribe = db.collection('orders').doc('order-001')
.onSnapshot((doc) => {
if (doc.exists) {
console.log('Order updated:', doc.data());
}
});
// Listen to a query (all pending orders)
const queryUnsubscribe = db.collection('orders')
.where('status', '==', 'pending')
.onSnapshot((snapshot) => {
snapshot.docChanges().forEach((change) => {
if (change.type === 'added') {
console.log('New order:', change.doc.data());
} else if (change.type === 'modified') {
console.log('Updated order:', change.doc.data());
} else if (change.type === 'removed') {
console.log('Removed order:', change.doc.id);
}
});
});
// Stop listening
// unsubscribe();
```
## Batch Writes and Transactions
```python
# Batch write (up to 500 operations)
batch = db.batch()
for i in range(100):
ref = db.collection('products').document(f'product-{i:04d}')
batch.set(ref, {
'name': f'Product {i}',
'price': round(9.99 + i * 0.5, 2),
'in_stock': True
})
batch.commit()
print("Batch write complete")
```
```python
# Transaction for atomic read-modify-write
@firestore.transactional
def transfer_funds(transaction, from_ref, to_ref, amount):
from_doc = from_ref.get(transaction=transaction)
to_doc = to_ref.get(transaction=transaction)
from_balance = from_doc.get('balance')
if from_balance < amount:
raise ValueError('Insufficient funds')
transaction.update(from_ref, {'balance': from_balance - amount})
transaction.update(to_ref, {'balance': to_doc.get('balance') + amount})
transaction = db.transaction()
transfer_funds(
transaction,
db.collection('accounts').document('alice'),
db.collection('accounts').document('bob'),
50.00
)
```
## Security Rules
```javascript
// firestore.rules — access control for client SDKs
rules_version = '2';
service cloud.firestore {
match /databases/{database}/documents {
// Users can read/write their own profile
match /users/{userId} {
allow read: if request.auth != null;
allow write: if request.auth.uid == userId;
}
// Orders: owner can read, only server can write
match /orders/{orderId} {
allow read: if request.auth.uid == resource.data.user_id;
allow create: if request.auth != null
&& request.resource.data.user_id == request.auth.uid
&& request.resource.data.total > 0;
allow update, delete: if false; // server-side only
}
// Public read, admin write
match /products/{productId} {
allow read: if true;
allow write: if request.auth.token.admin == true;
}
}
}
```
```bash
# Deploy security rules
firebase deploy --only firestore:rules
```
## Indexes
```json
// firestore.indexes.json — composite indexes for complex queries
{
"indexes": [
{
"collectionGroup": "orders",
"queryScope": "COLLECTION",
"fields": [
{"fieldPath": "status", "order": "ASCENDING"},
{"fieldPath": "total", "order": "DESCENDING"}
]
},
{
"collectionGroup": "orders",
"queryScope": "COLLECTION",
"fields": [
{"fieldPath": "user_id", "order": "ASCENDING"},
{"fieldPath": "created_at", "order": "DESCENDING"}
]
}
]
}
```
```bash
# Deploy indexes
firebase deploy --only firestore:indexes
```
## Best Practices
- Design data around your queries — denormalize for read performance
- Use subcollections for large lists that are always accessed per parent
- Keep documents small (<1MB); use subcollections for unbounded lists
- Use transactions for operations that need atomicity across documents
- Create composite indexes for queries with multiple where/orderBy clauses
- Use security rules for all client-accessible data — never trust the client
- Use batch writes for bulk operations (up to 500 per batch)
- Enable offline persistence for mobile apps with poor connectivityRelated Skills
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