Is it compatible with Supabase?

Yes, it is specifically optimized for ChravelApp's stack, using Supabase as the core serverless orchestration layer for Google services.

How does this skill handle Google API updates?

The skill follows a 'research-first' rule, prioritizing the latest official Google documentation and release notes over stale training data to ensure compatibility with current SDKs.

What is the Google Gemini Ecosystem Architect?

It is a specialized Claude Code skill that provides domain-specific guidance for researching, designing, and implementing Google’s entire AI and Cloud ecosystem.

Can it assist with Google OAuth verification?

Absolutely. It identifies required scopes and provides a readiness checklist for app verification, demo videos, and security assessments needed for production launch.

Does it support secret management?

Yes, it includes a dedicated secret-management framework for determining which credentials belong in client-side env vars versus Supabase Edge Function secrets.

Google Gemini Ecosystem Architect

Name: Google Gemini Ecosystem Architect
Author: MeechYourGoals

byMeechYourGoals

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Cloud Infrastructure

Architects and implements production-grade Google AI, Gemini models, and Cloud services with a focus on multimodal RAG and secure Supabase integration.

The Google Gemini Ecosystem Architect is a specialized skill for Claude Code designed to manage the full lifecycle of Google Cloud and AI integrations. It prioritizes official, up-to-date documentation to research, design, and deploy features using Gemini, Vertex AI, and the Google Maps Platform. The skill excels at navigating complex requirements like OAuth verification, IAM service account setup, and secret management within Supabase Edge Functions, ensuring that every implementation is not just functional code, but a shippable, production-ready architecture.

Key Features

01Supabase Edge Function orchestration and secret management

02Secure OAuth flow setup with sensitive scope verification readiness

03Latest Gemini & Vertex AI model implementation and SDK migration

04Multimodal RAG pipeline design for text, images, and documents

052 GitHub stars

06Comprehensive Google Cloud Console and IAM configuration guidance

Use Cases

01Implementing real-time grounding using Google Search and Maps Platform data

02Building secure integrations for Gmail, Calendar, and Drive within a serverless stack

03Upgrading existing AI features to the latest production-ready Gemini models

Key Features

01Supabase Edge Function orchestration and secret management

02Secure OAuth flow setup with sensitive scope verification readiness

03Latest Gemini & Vertex AI model implementation and SDK migration

04Multimodal RAG pipeline design for text, images, and documents

052 GitHub stars

06Comprehensive Google Cloud Console and IAM configuration guidance

Use Cases

01Implementing real-time grounding using Google Search and Maps Platform data

02Building secure integrations for Gmail, Calendar, and Drive within a serverless stack

03Upgrading existing AI features to the latest production-ready Gemini models