Skill UI

A comprehensive TypeScript SDK providing production-ready patterns for interacting with the Fly.io Machines REST API. It includes a typed client for managing the entire machine lifecycle—creation, state polling, and deletion—across multiple global regions. Features like robust error handling, rate-limit retries, and deployment builders ensure reliable multi-region orchestration for edge computing applications.

This integration facilitates the deployment of Hex orchestration services to major cloud platforms like Vercel, Google Cloud Run, and Fly.io. It is essential for setting up production environments, managing platform-specific secrets (like API tokens), and automating deployment pipelines for Hex-powered applications.

This guide details the recommended reference architecture and project structure for integrating with the Hex platform. It covers best practices for designing robust data pipelines, including components like orchestration layers (Airflow, Dagster), API clients, and standardized project layouts. Use this when starting new Hex integrations or reviewing complex data workflows.

A comprehensive skill for managing the entire lifecycle of Volcano Jobs within the KubeSphere environment. It supports the scheduling and execution of complex batch workloads, including deep learning tasks using PyTorch and TensorFlow, MPI, and general resource-intensive jobs. Provides detailed API usage and troubleshooting guidance for job scheduling and resource conflicts.

This skill provides a comprehensive, production-grade reference architecture for building robust Notion integrations. It defines a multi-layered structure, including client singletons, repository patterns, service orchestration, and caching mechanisms. It is essential for migrating ad-hoc API calls to scalable, event-driven, and highly reliable enterprise applications that incorporate rate limiting, sophisticated error handling, and comprehensive testing strategies.

This tool allows users to execute complex, multi-agent workflows defined in YAML format directly within the AI environment. It functions as an orchestration engine, sequentially invoking various specialized roles (agents) without requiring manual API key configuration. Ideal for structured tasks requiring collaboration between multiple personas.