Firebase AI Logic

When to use this skill

• Add Gemini-powered features directly inside a Firebase app.
• Build in-app text, chat, multimodal, structured-output, or streaming experiences.
• Decide whether a request should stay in the client/app layer or move to a backend workflow.
• Add Firebase-specific production controls such as App Check, quota awareness, and Firebase service integration around the AI feature.
• Handle app-side AI for web, mobile, Flutter, Unity, or similar Firebase-supported client surfaces.

Do not use this skill when

• The user needs server-owned flows, tool calling, RAG, evaluators, traces, prompt files, or reusable backend orchestration → use genkit.
• The user needs Firebase project setup, emulator, hosting/functions deploys, or CLI operations → use firebase-cli.
• The user is not committed to Firebase and mainly needs a generic provider SDK comparison → use a provider-specific or framework-selection skill instead.

Operating model

Treat firebase-ai-logic as the client/app integration anchor in a three-way lane:

1. App/client feature integration → firebase-ai-logic
2. Backend workflow orchestration → genkit
3. Firebase platform / operator tasks → firebase-cli