Skill UI

Specializes in the expert deployment and orchestration of production-grade multi-agent systems using Google's Agent Development Kit (ADK). This skill manages the complex lifecycle, including AgentCard discovery, A2A protocol communication, state management via Memory Bank, and secure execution within the Code Execution Sandbox. Ideal for setting up robust, enterprise-level AI workflows on the Vertex AI Agent Engine, especially during CI/CD pipelines.

Automated GCP skill that activates when you ask about BigQuery ML model creator tasks, delivering best-practice guidance, production-ready code, and validation for compute, storage, BigQuery, Vertex AI, and other platform services.

Generates complete, production-ready Google Cloud Platform (GCP) code examples and infrastructure templates. It spans various modern AI patterns, including ADK agents, Genkit RAG flows, and multimodal analysis using Vertex AI and Gemini. The output includes runnable code, deployment configuration (Terraform/IaC), security best practices (IAM, VPC-SC), and monitoring setup, ensuring enterprise-grade reliability and cost optimization.

Scaffolds production-ready generative AI agents on Vertex AI with Gemini models, multi-modal tools, RAG, and Cloud Run/Endpoint deployment, including observability and evaluation for enterprise scenarios.

Automates Vertex AI deployment tasks, offering step-by-step guidance, production-ready code, and validation for model serving, MLOps pipelines, monitoring, and optimization when you mention Vertex AI Deployer.

Automates Vertex AI endpoint configuration guidance, follows GCP best practices, and helps generate validated production-ready code and setup steps whenever you ask about endpoint config patterns.

Automates Vertex AI's multimodal media workflows—video understanding, image/audio generation, and marketing campaign assets—so teams can produce cross-channel creatives from a single prompt.

Provides automated guidance for designing, validating, and deploying Vertex AI pipelines within Google Cloud, covering compute, storage, BigQuery, and GCP-specific services for production readiness.

This skill thoroughly inspects and validates Vertex AI Agent Engine deployments. It assesses critical components such as the Code Execution Sandbox, Memory Bank, A2A protocol compliance, security posture, and performance metrics. The tool generates weighted production-readiness scores (0-100%) and provides detailed, actionable recommendations to ensure the deployment is robust, secure, and ready for production use.

Specializes in provisioning Vertex AI infrastructure with Terraform, covering Model Garden, Gemini endpoints, vector search indexes, ML pipelines, and enterprise-grade production deployments.

This skill provides comprehensive CLI commands for managing all AI integrations within the Arize platform. Users can list, retrieve, create, and delete credentials for various leading LLM providers (including OpenAI, Anthropic, AWS Bedrock, Vertex AI, Gemini, etc.). It is essential for ML engineers who need to configure and centralize access to external large language models for evaluation, monitoring, and advanced feature calling.