firebase-vertex-ai
Execute firebase platform expert with Vertex AI Gemini integration for Authentication, Firestore, Storage, Functions, Hosting, and AI-powered features. Use when asked to "setup firebase", "deploy to firebase", or "integrate vertex ai with firebase". Trigger with relevant phrases based on skill purpose.
Best use case
firebase-vertex-ai is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Execute firebase platform expert with Vertex AI Gemini integration for Authentication, Firestore, Storage, Functions, Hosting, and AI-powered features. Use when asked to "setup firebase", "deploy to firebase", or "integrate vertex ai with firebase". Trigger with relevant phrases based on skill purpose.
Teams using firebase-vertex-ai 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/firebase-vertex-ai/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How firebase-vertex-ai Compares
| Feature / Agent | firebase-vertex-ai | 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?
Execute firebase platform expert with Vertex AI Gemini integration for Authentication, Firestore, Storage, Functions, Hosting, and AI-powered features. Use when asked to "setup firebase", "deploy to firebase", or "integrate vertex ai with firebase". Trigger with relevant phrases based on skill purpose.
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
# 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
1. Initialize Firebase (or validate an existing repo): Hosting/Functions/Firestore as required.
2. Implement backend integration:
- add a Cloud Function/HTTP endpoint that calls Gemini/Vertex AI
- validate inputs and return structured responses
3. Configure data and security:
- Firestore rules + indexes
- Storage rules (if applicable)
- Auth providers and authorization checks
4. Deploy and verify:
- deploy Functions/Hosting
- run smoke tests against deployed endpoints
5. 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): `${CLAUDE_SKILL_DIR}/references/SKILL.full.md`
- Firebase docs: https://firebase.google.com/docs
- Cloud Functions for Firebase: https://firebase.google.com/docs/functions
- Vertex AI docs: https://cloud.google.com/vertex-ai/docsRelated Skills
vertex-ai-media-master
Automatic activation for ALL Google Vertex AI multimodal operations - video processing, audio generation, image creation, and marketing campaigns. **TRIGGER PHRASES:** - "vertex ai", "gemini multimodal", "process video", "generate audio", "create images", "marketing campaign" - "imagen", "video understanding", "multimodal", "content generation", "media assets" **AUTO-INVOKES FOR:** - Video processing and understanding (up to 6 hours) - Audio generation and transcription - Image generation with Imagen 4 - Marketing campaign automation - Social media content creation - Ad creative generation - Multimodal content workflows
vertex-infra-expert
Terraform infrastructure specialist for Vertex AI services and Gemini deployments. Provisions Model Garden, endpoints, vector search, pipelines, and enterprise AI infrastructure. Triggers: "vertex ai terraform", "gemini deployment terraform", "model garden infrastructure", "vertex ai endpoints"
vertex-engine-inspector
Inspect and validate Vertex AI Agent Engine deployments including Code Execution Sandbox, Memory Bank, A2A protocol compliance, and security posture. Generates production readiness scores. Use when asked to inspect, validate, or audit an Agent Engine deployment. Trigger with "inspect agent engine", "validate agent engine deployment", "check agent engine config", "audit agent engine security", "agent engine readiness check", "vertex engine health", or "reasoning engine status".
vertex-ai-pipeline-creator
Vertex Ai Pipeline Creator - Auto-activating skill for GCP Skills. Triggers on: vertex ai pipeline creator, vertex ai pipeline creator Part of the GCP Skills skill category.
vertex-ai-endpoint-config
Vertex Ai Endpoint Config - Auto-activating skill for GCP Skills. Triggers on: vertex ai endpoint config, vertex ai endpoint config Part of the GCP Skills skill category.
vertex-ai-deployer
Vertex Ai Deployer - Auto-activating skill for ML Deployment. Triggers on: vertex ai deployer, vertex ai deployer Part of the ML Deployment skill category.
vertex-agent-builder
Build and deploy production-ready generative AI agents using Vertex AI, Gemini models, and Google Cloud infrastructure with RAG, function calling, and multi-modal capabilities
firebase-rules-generator
Firebase Rules Generator - Auto-activating skill for GCP Skills. Triggers on: firebase rules generator, firebase rules generator Part of the GCP Skills skill category.
firebase-ai-logic
Integrate Firebase AI Logic (Gemini in Firebase) for intelligent app features. Use when adding AI capabilities to Firebase apps, implementing generative AI features, or setting up Firebase AI SDK. Handles Firebase AI SDK setup, prompt engineering, and AI-powered features.
firebase-development-project-setup
This skill should be used when initializing a new Firebase project with proven architecture. Triggers on "new firebase project", "initialize firebase", "firebase init", "set up firebase", "create firebase app", "start firebase project". Guides through CLI setup, architecture choices, and emulator configuration.
firebase-development
This skill should be used when working with Firebase projects, including initializing projects, adding Cloud Functions or Firestore collections, debugging emulator issues, or reviewing Firebase code. Triggers on "firebase", "firestore", "cloud functions", "emulator", "firebase auth", "deploy to firebase", "firestore rules".
firebase-development-validate
This skill should be used when reviewing Firebase code against security model and best practices. Triggers on "review firebase", "check firebase", "validate", "audit firebase", "security review", "look at firebase code". Validates configuration, rules, architecture, and security.