Skill UI

This guide provides a comprehensive walkthrough for setting up and authenticating with the OpenRouter API. It covers generating secure API keys, configuring environment variables, and initializing clients in Python and TypeScript. Learn best practices for secure integration, including key management, verification, and key rotation, ensuring reliable connectivity to various large language models (LLMs).

This skill provides comprehensive tools to monitor the real-time availability, status, and performance of various large language models (LLMs) accessed via OpenRouter. It supports active health probes, catalog checks, and scheduled monitoring via Python and Bash, ensuring robust fault detection and failover logic for production systems that rely on external AI APIs.

This skill provides comprehensive best practices and Python code examples for optimizing API calls to Large Language Models (LLMs) via OpenRouter. It covers benchmarking model latency, implementing streaming to achieve low Time-To-First-Token (TTFT), and processing requests concurrently using asynchronous programming (asyncio). Use this when developing real-time, high-throughput applications that require predictable and fast model responses.

This skill provides comprehensive guides on implementing real-time streaming responses using OpenRouter's Server-Sent Events (SSE) capability. It covers various languages (Python, TypeScript, FastAPI, JavaScript), enabling developers to build modern, fast-feeling chat interfaces. By streaming tokens as they are generated, it significantly reduces the time-to-first-token (TTFT) and improves user experience for long completions and chat applications.

This guide provides a comprehensive overview of PDF manipulation techniques using both Python libraries (like pypdf, pdfplumber, reportlab) and command-line tools (like pdftotext, qpdf). It covers core functionalities such as merging, splitting, rotating, extracting text and structured tables, creating new PDFs, and performing OCR on scanned documents, making it essential for automation workflows.

This tool is designed to collect comprehensive diagnostic evidence for troubleshooting Perplexity API issues. It automatically gathers critical environment details (OS, Node/Python versions), tests API connectivity, and captures redacted configuration settings. The resulting secure bundle is ideal for submitting detailed support tickets or sharing with technical teammates.

Provides a minimal working example demonstrating how to integrate Perplexity's API for web-grounded answers. Learn to perform advanced searches, retrieve cited sources, and handle features like domain filtering and streaming using both TypeScript and Python. Ideal for integrating real-time, source-backed search functionality into applications.

This guide provides comprehensive instructions for installing and configuring the Perplexity Sonar API authentication. It details setting up the necessary environment variables and using the standard OpenAI client library (for both Node.js and Python) to connect to Perplexity's API endpoint. Learning this process is essential for developers starting a new Perplexity integration, setting up API keys, or verifying API connectivity.

A comprehensive guide and implementation examples for handling API rate limits (HTTP 429) when interacting with the Perplexity Sonar API. This resource provides multiple robust techniques, including exponential backoff with jitter, queue-based rate limiting, and custom Token Bucket implementation, ensuring reliable and high-throughput API calls for developers using TypeScript and Python.

Automates the collection of comprehensive diagnostic evidence for PostHog support tickets. This bundle gathers runtime environment details (Node, Python versions), SDK versions, API connectivity status to US/EU clouds, feature flag settings, event flow testing results, and redacts sensitive environment variables. It provides a structured, support-ready archive for rapid troubleshooting.

This skill guides the complete setup and configuration of PostHog SDKs for modern applications. It covers best practices for implementing client-side (browser) and server-side (Node.js/Python) event tracking. Users will learn how to install the necessary SDKs via npm or pip, manage environment variables for both Project API Keys and secure Personal API Keys, and initialize the tracking service correctly to ensure accurate and reliable event capture in PostHog.

A comprehensive guide to implementing production-ready patterns for PostHog analytics integration. This includes establishing singleton clients for both server-side (Python/Node) and client-side environments. It provides type-safe event capture utilities, React hooks for handling feature flags (including variants), and the full Next.js App Router setup for robust pageview tracking. Patterns are available for both TypeScript/JavaScript and Python environments.