Agent-Skills.md

Agent Skills: Firebase Vertex AI

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UncategorizedID: jeremylongshore/claude-code-plugins-plus-skills/firebase-vertex-ai

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jeremylongshore/claude-code-plugins-plus-skills
jeremylongshoreLicense: NOASSERTION
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pnpm dlx add-skill https://github.com/jeremylongshore/claude-code-plugins-plus-skills/tree/HEAD/plugins/community/jeremy-firebase/skills/firebase-vertex-ai

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plugins/community/jeremy-firebase/skills/firebase-vertex-ai/SKILL.md

Skill Metadata

Name
firebase-vertex-ai
Description
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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

  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/docs