Installation

Open Claude Code and run this command:

/plugin install jeremy-firebase@claude-code-plugins-plus

Use --global to install for all projects, or --project for current project only.

What It Does

Comprehensive automation for Firebase services including Authentication, Cloud Storage, Hosting, Cloud Functions, Analytics, and AI-powered features using Vertex AI Gemini.

Features

Core Firebase Services

Firebase Authentication - User management, custom claims, OAuth providers
Cloud Firestore - Document CRUD, queries, security rules, indexes
Cloud Storage - File uploads, security rules, signed URLs
Firebase Hosting - Static site deployment, custom domains, SSL
Cloud Functions - TypeScript/JavaScript functions, HTTP/callable/scheduled triggers
Firebase Analytics - Event logging, user properties, conversion tracking

AI Integration (Vertex AI Gemini)

Embeddings Generation - Text-to-vector for semantic search
Content Analysis - Gemini API for content moderation, classification
Chat Integration - Conversational AI with Firebase data context
Model Deployment - Custom AI models with Firebase ML
RAG Implementation - Retrieval-Augmented Generation with Firestore vector search

DevOps & Operations

Firebase CLI Automation - Project init, deployment, emulator control
Environment Management - Multiple Firebase projects (dev, staging, prod)
Security Rules Testing - Automated testing of Firestore and Storage rules
Performance Monitoring - Integration with Firebase Performance Monitoring
Remote Config - Feature flags and A/B testing setup

Skills (1)

firebase-vertex-ai SKILL.md View full skill →

Execute firebase platform expert with Vertex AI Gemini integration for Authentication, Firestore, Storage, Functions, Hosting, and AI-powered features.

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Firebase Vertex AI

Operate Firebase projects end-to-end (Auth, Firestore, Functions, Hosting) and integrate Gemini/Vertex AI safely for AI-powered features.

Overview

Use this skill to design, implement, and deploy Firebase applications that call Vertex AI/Gemini from Cloud Functions (or other GCP services) with secure secrets handling, least-privilege IAM, and production-ready observability.

Prerequisites

Node.js runtime and Firebase CLI access for the target project
A Firebase project (billing enabled for Functions/Vertex AI as needed)
Vertex AI API enabled and permissions to call Gemini/Vertex AI from your backend
Secrets managed via env vars or Secret Manager (never in client code)

Instructions

Initialize Firebase (or validate an existing repo): Hosting/Functions/Firestore as required.
Implement backend integration:

add a Cloud Function/HTTP endpoint that calls Gemini/Vertex AI
validate inputs and return structured responses

Configure data and security:

Firestore rules + indexes
Storage rules (if applicable)
Auth providers and authorization checks

Deploy and verify:

deploy Functions/Hosting
run smoke tests against deployed endpoints

Add ops guardrails:

logging/metrics
alerting for error spikes
basic cost controls (budgets/quotas) where appropriate

Output

A deployable Firebase project structure (configs + Functions/Hosting as needed)
Secure backend code that calls Gemini/Vertex AI (with secrets handled correctly)
Firestore/Storage rules and index guidance
A verification checklist (local + deployed) and CI-ready commands

Error Handling

Auth failures: identify the principal and missing permission/role; fix with least privilege.
Billing/API issues: detect which API or quota is blocking and provide remediation steps.
Firestore rule/index problems: provide minimal repro queries and rule fixes.
Vertex AI call failures: surface model/region mismatches and add retries/backoff for transient errors.

Examples

Example: Gemini-backed chat API on Firebase

Request: “Deploy Hosting + a Function that powers a Gemini chat endpoint.”
Result: /api/chat function, Secret Manager wiring, and smoke tests.

Example: Firestore-powered RAG

Request: “Build a RAG flow that embeds docs and answers with citations.”
Result: ingestion plan, embedding + index strategy, and evaluation prompts.

Resources

Full detailed guide (kept for reference): ${CLAUDESKILLDIR}/references/SKILL.full.md

How It Works

Initialize Firebase Project


firebase login
firebase init

Deploy to Firebase

Use the slash commands:


/firebase-deploy-hosting
/firebase-deploy-functions
/firebase-deploy-rules

Environment Configuration

Create .env.local:


FIREBASE_PROJECT_ID=your-project-id
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json
VERTEX_AI_LOCATION=us-central1

FAQ

Common Issues

Issue: Firebase CLI not found


npm install -g firebase-tools

Issue: Authentication failed


firebase login --reauth

Issue: Vertex AI quota exceeded

Check quotas in GCP Console
Implement rate limiting in Cloud Functions
Use caching to reduce API calls

Issue: Firestore permissions denied

Check security rules in Firebase Console
Verify user is authenticated
Review IAM permissions

jeremy-firebase

Installation

What It Does

Features

Core Firebase Services

AI Integration (Vertex AI Gemini)

DevOps & Operations

Skills (1)

Firebase Vertex AI

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Resources

How It Works

Initialize Firebase Project

Deploy to Firebase

Environment Configuration

FAQ

Ready to use jeremy-firebase?

Related Plugins

jeremy-firebase

Installation

What It Does

Features

Core Firebase Services

AI Integration (Vertex AI Gemini)

DevOps & Operations

Skills (1)

Firebase Vertex AI

Overview

Prerequisites

Instructions

Output

Error Handling

Examples

Resources

How It Works

Initialize Firebase Project

Deploy to Firebase

Environment Configuration

FAQ

Ready to use jeremy-firebase?

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