Skill UI

A set of production-ready wrappers and patterns for interacting with the CAST AI REST API. This package provides robust client implementations in TypeScript and Python, handling critical features such as typed responses, singleton management, automatic retry logic with backoff, and managing cloud resources (e.g., Kubernetes clusters, node optimization). Use it when building reusable, reliable clients for cost optimization and infrastructure management.

A comprehensive reference guide for diagnosing and fixing common Anthropic Claude API errors, categorized by HTTP status codes (400, 429, 500, etc.). Includes specific error JSON patterns, root causes (e.g., role alternation, rate limits), suggested fixes, and code examples in Bash and Python for effective troubleshooting.

A comprehensive guide and set of scripts for performing load testing and capacity planning for Anthropic's Claude API. This resource helps developers benchmark performance, anticipate traffic spikes, manage rate limits (RPM/ITPM/OTPM), and implement robust horizontal scaling strategies for mission-critical AI services using Python.

This comprehensive guide walks through setting up Adobe Developer Console OAuth Server-to-Server credentials. It is critical for establishing any new programmatic integration with Adobe services, including Firefly AI, PDF processing, and Creative Cloud access. The process covers project setup, installing various SDKs (Node.js/Python), and securely generating access tokens.

A comprehensive guide to production-ready patterns for integrating with Adobe services (Firefly, PDF, etc.). This includes robust authentication with token caching, typed API wrappers with advanced error classification, exponential backoff retry mechanisms, and job polling for asynchronous tasks. Essential for building reliable and maintainable Adobe API integrations in TypeScript or Python.

A comprehensive guide for configuring and managing organization-level access control within the Anthropic ecosystem. It details Workspaces setup (Production, Staging, Development), defines roles (Owner, Admin, Developer), and provides best practices for API key management. Includes practical Python code examples for implementing application-level Role-Based Access Control (RBAC) to restrict model access and usage limits.

This resource provides production-ready architectural patterns for integrating Anthropic's Claude models using TypeScript and Python. It covers robust client wrappers, managing multi-turn conversations, enforcing structured JSON output via prefilling, and implementing multi-tenant architectures. Essential for building reliable, enterprise-grade AI applications.

A comprehensive guide detailing how to upgrade Anthropic SDKs (Python/TypeScript) and manage API version transitions. Learn to migrate from Text Completions to the Messages API, incorporate new features like tool use, and handle common breaking changes across major SDK versions.

This guide provides production-ready architectural patterns for integrating the AssemblyAI SDK in TypeScript and Python. It details best practices including implementing Singleton clients, robust service wrappers, advanced error handling (like exponential backoff retries), and multi-tenant client management. Use this when building highly scalable and reliable speech-to-text applications.

A comprehensive utility designed to collect all necessary diagnostic evidence for troubleshooting BambooHR API issues or preparing detailed support tickets. It captures runtime environment information (Node.js, Python, OS), performs connectivity tests against core endpoints (e.g., employees, time off), and gathers redacted API response details, making it essential for efficient bug reporting.

This module provides production-ready, type-safe patterns for interacting with the BambooHR REST API, supporting TypeScript and Python. It wraps raw HTTP calls into robust, retry-aware clients, handling complex tasks like error management and multi-tenancy. Use this when building reliable, enterprise-grade integrations with BambooHR.

This comprehensive guide details the end-to-end process for integrating Bright Data into development projects. It covers gathering zone credentials, setting up environment variables, downloading necessary SSL certificates, and configuring both Node.js and Python environments for robust and reliable web scraping proxy authentication.