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.

Expertise in building production-grade LLM applications, advanced Retrieval-Augmented Generation (RAG) systems, and complex intelligent agents. This skill covers the entire AI lifecycle, including model orchestration, vector search optimization, multimodal integration (vision/audio), MLOps deployment, and robust safety governance for enterprise-level AI solutions.

Expertise in building production-grade LLM applications, advanced Retrieval-Augmented Generation (RAG) systems, and complex intelligent agents. This skill covers the entire AI lifecycle, including model orchestration, vector search optimization, multimodal integration (vision/audio), MLOps deployment, and robust safety governance for enterprise-level AI solutions.

A comprehensive guide focused on mastering the Entity Component System (ECS) architecture within the Bevy game engine using Rust. Learn best practices for building high-performance, data-oriented game logic. This covers defining components, writing parallel systems, managing global resources, and optimizing queries for efficient, scalable game development.

This advanced skill analyzes an existing codebase to identify architectural patterns, dependencies, and technical stacks. It recommends tailored Claude Code automations—including Hooks, Subagents, Skills, Plugins, and MCP Servers—to optimize development workflows, improve code consistency, and enhance overall project scalability. Use this when setting up a new project or looking to refine existing Claude Code configurations.

This expert analyzes and refactors existing codebases to enhance quality, maintainability, and performance. It specializes in applying clean code principles, SOLID design patterns, and modern software engineering best practices. Use it to clean up technical debt, simplify complex modules, or prepare a codebase for new feature development.

A comprehensive, end-to-end workflow for building product features guided by rigorous data insights. This skill guides users through the entire lifecycle, encompassing exploratory data analysis, forming measurable business hypotheses, designing statistical A/B tests, architecting data pipelines, and implementing robust backend/frontend instrumentation. It ensures that every feature iteration is validated by data and measured for impact.

A comprehensive guide to setting up a minimal working example on Databricks. This skill covers creating a development cluster, uploading and executing notebooks (Python SDK), running tasks as jobs, and setting up a Serverless SQL Warehouse. It is ideal for new users or initializing a basic data engineering project.

A comprehensive guide to setting up a fast, isolated local development loop for data engineering projects using Databricks Connect v2, Asset Bundles, and standard IDEs (like VS Code). This workflow allows developers to run PySpark code locally for debugging and unit testing, while managing resource deployment and ensuring consistency across development, staging, and production environments.

This skill defines a senior engineer specializing in the entire software development lifecycle (SDLC). It covers building robust CI/CD pipelines (e.g., GitHub Actions), containerizing applications with Docker, and managing infrastructure using Infrastructure as Code (IaC) tools like Terraform or Pulumi. Key areas include Kubernetes deployment (GitOps), cloud platform configuration (AWS/GCP/Azure), release automation, and incident response planning.

This comprehensive guide establishes strict architectural and performance standards for senior frontend engineers working with React, TypeScript, and Suspense. It dictates best practices for component design, feature implementation, data fetching (useSuspenseQuery), and code structure (feature-based organization). Use this when building any new component, feature, or handling data mutation to ensure the resulting application is scalable, predictable, and maintainable.