Skill UI

This expert specializes in scaffolding complete, production-ready, accessible, and performant React and React Native components. It generates full boilerplate code including TypeScript definitions, unit tests, styles (CSS Modules, Styled-Components, Tailwind), and accessibility hooks, ensuring adherence to modern best practices for scalable frontend architecture.

A comprehensive toolkit designed to systematically diagnose and troubleshoot integration issues with the Gamma API. It includes scripts for connectivity testing, authentication validation, latency measurement, and checking various API endpoints (themes, folders, generations) across both Bash and TypeScript environments. Essential for developers ensuring reliable API connections.

This skill provides a comprehensive set of reusable, production-grade TypeScript patterns for interacting with the Gamma REST API, which lacks an official SDK. It includes implementation for typed clients, advanced polling mechanisms, structured error handling, and complex generation workflows (e.g., template-based generation). Use this when building robust, reliable applications that integrate deeply with Gamma's content generation services.

This skill generates robust, type-safe client Software Development Kits (SDKs) for multiple languages (including Python, TypeScript, Go, and Java) directly from OpenAPI 3.0+ specifications. It automatically handles complex API patterns such as authentication (Bearer, OAuth2), automatic retries with exponential backoff, and sophisticated pagination helpers. Use this when you need to create standardized, idiomatic client libraries to consume a defined API contract across diverse development stacks.

A comprehensive guide detailing common Groq API error codes (e.g., 401, 429, 400). It provides root causes, proper fixes, and code examples (Python, TypeScript) for debugging API integrations, ensuring stable operation in development environments.

A comprehensive guide to using Groq's high-speed LPU for chat completion. This resource provides code examples in TypeScript and Python, covering basic chat interactions, streaming responses, and advanced multimodal features. Ideal for developers building high-performance, low-latency AI applications using the Groq API.

This guide provides comprehensive instructions for installing and configuring the official Groq SDK in both Python and TypeScript environments. It covers dependency setup, secure API key management using environment variables, and provides code examples to verify a successful connection to Groq's ultra-fast LLM inference API. Essential for initiating any project powered by Groq.

A comprehensive guide to production-ready patterns for using the Groq SDK in TypeScript and Python. Covers best practices for client singleton setup, type-safe completions, streaming, robust error handling (rate limiting, API errors), and implementing exponential backoff retries to ensure stable, high-performance LLM integration.

A comprehensive guide demonstrating how to generate your first AI image using the Ideogram API. It provides runnable examples in cURL, TypeScript, and Python, covering both legacy and V3 endpoints. Users will learn essential API parameters, such as prompt structuring, style types, and aspect ratios, making it ideal for initial integration testing and setup.

A comprehensive guide to setting up and authenticating the Ideogram API for AI image generation. This skill covers obtaining the necessary API key, configuring environment variables, and providing verifiable code snippets (Python/TypeScript) to establish a successful connection. It is essential for integrating image generation, editing, and remixing capabilities into any development project.

A comprehensive guide to implementing robust observability for Ideogram AI image generation APIs. Learn how to track critical metrics such as generation duration (latency), estimated API costs, error rates, and content safety rejections. This skill involves instrumenting API calls using TypeScript, integrating cost estimation, and setting up Prometheus alerting rules to ensure stable and reliable AI operation.

This document provides production-grade patterns for integrating with the Ideogram API in TypeScript and Python. It addresses common challenges in API usage, including implementing singleton client management, robust exponential backoff retry logic for rate limiting, and strict response validation using libraries like Zod. Use this guide when building reliable, scalable applications that depend on external AI image generation services.