What Google Cloud services does this skill utilize?

The skill primarily uses Vertex AI, Gemini models, and the Agent Engine runtime. For RAG capabilities, it integrates with GCS, BigQuery, or Firestore for document storage and indexing.

Does it include cost and quota management?

Yes, the output includes operational guidance for monitoring logs/metrics and setting up quota/cost guardrails to ensure production stability.

Does it support multimodal AI models?

Yes, it includes specialized patterns for building multimodal intake agents that can extract structured fields from files like PDFs and images using Gemini.

Can I build RAG-enabled agents with this skill?

Yes, it provides a comprehensive workflow for implementing Retrieval-Augmented Generation, including chunking strategies, embedding indexing, and citation-first response formats.

How does the skill handle agent deployment?

It provides exact deployment commands and configurations for Vertex AI Agent Engine, along with post-deployment health checks to verify endpoints and permissions.

Vertex AI Agent Builder

Name: Vertex AI Agent Builder
Author: jeremylongshore

byjeremylongshore

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883

Cloud Infrastructure

Builds and deploys production-ready generative AI agents using Vertex AI, Gemini models, and Google Cloud infrastructure.

About

The Vertex AI Agent Builder skill enables developers to create sophisticated, production-grade AI agents within the Google Cloud ecosystem. It automates the scaffolding process for Vertex AI Agent Engine, facilitates RAG implementation with complex data sources, and ensures robust tool integration through structured function calling. By incorporating evaluation checklists and operational guardrails like cost monitoring and performance metrics, this skill helps bridge the gap between experimental LLM prompts and reliable enterprise-scale AI deployments.

Key Features

Multimodal capability integration for PDF and image processing
Automated Vertex AI Agent Engine scaffolding and deployment
883 GitHub stars
RAG workflow implementation with citation-first response formatting
Structured tool and function interface design with error contracts
Integrated evaluation checklists and post-deploy smoke tests

Use Cases

Deploying RAG-based customer support bots with source citations
Building multimodal document processing agents for structured data extraction
Designing complex agents with backend function calling and operational guardrails

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jeremylongshore/claude-code-plugins-plus-skills vertex-agent-builder

For use in Claude.ai and ChatGPT

Download Skill

GitHub