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.

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.

Provides steps to automate Adobe tasks via Composio's Adobe toolkit using Rube MCP, emphasizing discovery of current tool schemas, connection verification, and compliant execution flows for reliable workflows.

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.

Guide to automate Adrapid operations through Composio's toolkit using Rube MCP, covering prerequisites, tool discovery, execution patterns, and best practices for schema compliance, connection checks, and session reuse.

Guides connecting Rube MCP to Composio’s Adyntel toolkit, searching for live tool schemas, validating connections, and executing multi-tool workflows while handling session reuse, memory, and pagination requirements.

Automate Aeroleads operations via Composio’s toolkit using Rube MCP: search for current tool schemas, confirm active connections, and invoke multi-tool executions with schema-compliant arguments and session handling.

AFL++ is an advanced fork of AFL that runs multi-core campaigns, supports diverse mutations, and targets large C/C++ codebases with stable tooling via Docker or host builds.

Automatically detects and loads specialized agent instructions from the `AGENTS.md` file in the current working directory. This skill seamlessly integrates project-specific rules and behavioral guidelines into the AI's session context, ensuring the AI operates according to project standards without manual intervention. It is crucial for maintaining specialized agent behaviors across different development tasks and directory changes.

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.