Skill UI

Automates creation of A/B test configurations for ML deployment, guiding users through best practices, code samples, and validation steps so production models are served with monitoring and rollout control.

Automates guidance for frontend accessibility audit runners, triggering on relevant requests and offering best practices, production-ready snippets, and validation against accessibility standards.

Generates and iterates high-performing ad creative—headlines, descriptions, primary text, and full variations—for any platform, using performance data to discover winning angles, stay within platform specs, and scale creative production.

Generates production-ready Claude-powered agents with Google’s ADK, bundling React-style loops, tool-augmented capabilities, multi-agent orchestration, workflow automation, and test scaffolding.

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.

A specialized skill for architecting, building, and productionizing complex Agent Development Kit (ADK) agents and multi-agent systems. This process emphasizes best practices, including clean module structure, robust tool integration, comprehensive regression testing, and deployment automation for reliable, shippable AI solutions. Use this when requiring the creation of structured, enterprise-grade agent code.

Provision production-grade Vertex AI ADK Agent Engine infrastructure with Terraform, covering Agent Engine runtime, code execution sandbox, Memory Bank, VPC Service Controls, and secure IAM setup for multi-agent deployments.

Automates architecture decision record (ADR) generation and guidance within technical documentation workflows, offering best-practice patterns, production-ready snippets, and validation for API docs, user guides, and automation needs.

A comprehensive tool for designing, generating schemas, and evaluating complex multi-agent systems. It guides users through defining system requirements, selecting optimal orchestration patterns (Supervisor, Swarm, Pipeline), generating provider-ready tool schemas (Anthropic/OpenAI), and analyzing execution logs for performance bottlenecks, cost, and latency. This ensures robust, production-grade autonomous workflows.

A comprehensive framework for rigorously testing and benchmarking LLM agents. It moves beyond simple pass/fail checks to assess complex behaviors, reliability metrics, and capability consistency across multiple runs. Ideal for production monitoring and identifying subtle failure modes in advanced AI agents.

This SDK allows developers to build persistent, sophisticated AI agents directly on Azure AI Foundry. It supports complex conversational workflows by integrating external functions (tools), enabling code execution, web search, and maintaining conversation history through dedicated thread management. Ideal for developing enterprise-grade, production-ready AI applications.

Utilizes the Azure AI Projects SDK's ImageBasedHostedAgentDefinition to build robust, container-based AI agents deployed in Azure AI Foundry. This workflow is essential for creating production-grade agents that require custom logic, precise resource allocation (CPU/Memory), and integration of advanced tools like code interpreters.