Skill UI

A comprehensive guide covering fundamental principles for creating 2D games. It details best practices for sprite organization (atlases, animation), tilemap design, physics implementation (collision shapes, fixed timestep), camera systems (follow, look-ahead), and genre-specific patterns like platformers and top-down games. Essential for game developers building robust 2D experiences.

A comprehensive guide covering core principles for building high-performance 3D game systems. Topics include the rendering pipeline, shader types, physics collision detection, camera control, and advanced optimization techniques like Frustum Culling and LOD. Ideal for developers needing to build visually rich and technically robust 3D environments.

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.

A comprehensive, multi-phase workflow designed for building sophisticated AI systems. This guide covers everything from designing autonomous agents and implementing single-agent logic, to orchestrating complex multi-agent systems and integrating advanced tools and memory mechanisms. Ideal for developers building production-grade AI applications using frameworks like CrewAI and LangGraph.

A comprehensive, multi-phase workflow designed for building sophisticated AI systems. This guide covers everything from designing autonomous agents and implementing single-agent logic, to orchestrating complex multi-agent systems and integrating advanced tools and memory mechanisms. Ideal for developers building production-grade AI applications using frameworks like CrewAI and LangGraph.

This skill covers the comprehensive architecture design and construction of autonomous AI agents. Experts master advanced concepts including tool use, hierarchical memory systems (episodic, semantic, working), sophisticated planning strategies (ReAct, Plan-and-Execute), and multi-agent orchestration. It focuses on building systems that achieve high levels of autonomy while maintaining critical human oversight, designing for graceful degradation and rigorous error handling.

This skill covers the comprehensive architecture design and construction of autonomous AI agents. Experts master advanced concepts including tool use, hierarchical memory systems (episodic, semantic, working), sophisticated planning strategies (ReAct, Plan-and-Execute), and multi-agent orchestration. It focuses on building systems that achieve high levels of autonomy while maintaining critical human oversight, designing for graceful degradation and rigorous error handling.

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, multi-phased workflow bundle designed for building production-grade AI and Machine Learning applications. It guides users through key stages, including AI application design, RAG implementation, autonomous agent development, robust ML pipelines, AI observability setup, and security hardening.

A comprehensive, multi-phased workflow bundle designed for building production-grade AI and Machine Learning applications. It guides users through key stages, including AI application design, RAG implementation, autonomous agent development, robust ML pipelines, AI observability setup, and security hardening.

A comprehensive guide to building production-ready Apache Airflow Directed Acyclic Graphs (DAGs). This skill covers best practices for operators, sensors, testing, deployment, and designing robust data pipelines. Use this when orchestrating complex workflows, managing ETL processes, or ensuring reliable batch job execution in a production environment.