Skill UI

Automates Chart.js configuration workflows with best-practice guidance, code generation, and validation so you can quickly build diagrams, presentations, and other visual content when requesting a chart js config creator.

Automatically assists with generating Content Security Policies, offering step-by-step guidance, production-ready code, and validation against common standards whenever you mention or ask about CSP generation.

This skill provides the production-ready reference architecture for integrating Exa into complex applications. It covers advanced search pipelines, RAG implementation for context generation, and structured content discovery. Use this to design new Exa integrations, review project structures, or establish industry-standard best practices for neural search systems.

A comprehensive reference guide for developers to debug and resolve common errors encountered when integrating with the Gamma API. Covers specific error codes such as authentication failures (401/403), rate limit issues (429), content generation failures, and timeouts. Provides detailed solutions, best practices, and code snippets for robust error handling and reliable API usage.

This comprehensive guide provides step-by-step instructions for setting up and authenticating with the Gamma Generate API v1.0. It covers generating the required API key, configuring environment variables, and executing initial connection tests using `curl` or code snippets in Node.js and Python. Essential for developers integrating Gamma's content generation capabilities into their applications.

This guide provides a deep dive into migrating existing presentation content (from PowerPoint, Google Slides, Canva, etc.) to the modern, AI-powered format of Gamma. It details a robust, multi-step workflow: content extraction, content cleaning, and batch regeneration using scripting methods. This approach ensures that the core content is preserved while benefiting from Gamma's superior AI formatting capabilities, moving beyond simple file imports and guaranteeing better results than the original source files.

This comprehensive guide details advanced strategies for optimizing interactions with the Gamma API. It covers critical best practices including implementing smart polling with adaptive backoff, caching static resources (themes, folders), executing parallel batch generations, and minimizing generation latency by tuning content parameters. Essential for developers building robust and high-performance Gamma integrations.

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 guide demonstrates how to build a resilient, event-driven architecture for Gamma API integrations when native webhooks are unavailable. It utilizes a poll-based pattern, creating synthetic application-level events (start, completed, failed) by wrapping polling logic within an EventEmitter or message queue. Ideal for building background workers that reliably track and react to the full lifecycle of content generation.

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 skill guides developers on building scalable, event-driven pipelines around Ideogram's synchronous API. It demonstrates implementing robust async patterns, including using job queues (like BullMQ) for batch generation, handling webhook callbacks for post-processing, and setting up full asset modification pipelines. Ideal for production-grade marketing and content workflows.

This tool provides comprehensive Python solutions for processing batches of text-to-video requests using the Kling AI API. It handles controlled parallelism, rate-limiting, and detailed status tracking. Use this when building robust content pipelines that require generating multiple videos efficiently from a list of prompts, supporting synchronous, asynchronous, and webhook callback methods.