Skill UI

This skill provides the core mechanism for integrating Hex into external data pipelines. It enables triggering, monitoring, and managing Hex projects (e.g., via Airflow or Dagster) programmatically. Users can implement parameterized runs, execute multi-step ETL workflows sequentially, and handle status polling and error management, making it ideal for production data orchestration.

This guide provides production-ready patterns for integrating with the Hex platform API using TypeScript and Python. It covers essential best practices like robust retry logic, typed client usage, pipeline orchestration, and Airflow integration, helping developers establish standardized, reliable coding standards for complex Hex workflows.

This integration automates the critical process of converting design assets from Figma into production-ready code using Anima. It establishes a full CI/CD pipeline via GitHub Actions, enabling scheduled or manual component generation. Use this when automating design system handoffs, maintaining code synchronization with design changes, or implementing robust, reliable development workflows.

This SDK provides production-ready TypeScript patterns for integrating with the AppFolio property management REST API. It includes a singleton client for centralized credential management, robust error wrappers (handling 429 rate limits and 401 auth errors), a flexible query builder for filtering data, and structured interfaces for core entities like Properties, Tenants, and Leases. Use it to build reliable, scalable automation workflows for real estate operations.

This library provides production-ready, type-safe patterns for automating Apple Notes management on macOS. Using JXA and AppleScript wrapped in a Node.js client, it allows developers to easily list, create, search, and perform batch operations on notes, complete with robust error handling and throttling for reliable workflow integration.

This guide details the process of deploying production-grade inference services on CoreWeave using KServe. It covers setting up autoscaling, GPU scheduling, and implementing scale-to-zero functionality for efficient ML model serving endpoints. Ideal for MLOps engineers deploying large language models (LLMs) or other complex AI models in a production environment.

This guide details setting up and managing CoreWeave GPU cloud infrastructure across Development, Staging, and Production environments. It ensures strict resource separation using dedicated Kubernetes namespaces for GPU quotas and scaling policies. Use this when deploying complex ML/AI workloads requiring robust environment isolation and controlled promotion workflows.

This SDK provides production-ready Python patterns for managing GPU workloads on CoreWeave. It includes helpers for defining specific GPU affinity, setting resource limits (A100, H100), and generating complete Kubernetes Deployment YAML. Use this library for building robust inference clients, managing GPU deployments programmatically, or automating complex AI workflows.

A comprehensive reference architecture for building production-grade integrations with the Figma REST API. This guide covers the full design-to-code pipeline, including design token extraction, scalable asset export (icons/images), and robust webhook event handling. Ideal for architects planning new Figma services, establishing project structure, or implementing complex design system workflows.

This skill provides comprehensive CI/CD pipeline setup for Fly.io edge deployments. It automates unit testing on pull requests, deploys to staging environments, and promotes changes to production upon merging to the main branch. It handles Docker builds, uses flyctl for deployment, and includes health checks to ensure service reliability and seamless automated delivery.

A comprehensive guide to managing the full application lifecycle on Fly.io. This workflow covers deploying applications, configuring the environment using fly.toml, managing sensitive secrets, scaling resources across multiple regions, and controlling the application's operational state (including suspension and destruction). Ideal for setting up production-grade, resilient cloud services.

This skill guides users through setting up robust, production-grade infrastructure on Fly.io. It covers creating and connecting to Fly Postgres clusters for reliable data storage, provisioning persistent NVMe Volumes for durable file storage, and configuring private internal networking (6PN) for secure service-to-service communication. It is essential for modern microservices requiring stable databases and persistent state.