Skill UI

This guide provides comprehensive documentation and code examples for integrating OpenEvidence webhooks. Learn how to subscribe to real-time events (e.g., query completion, evidence updates, new citations) to keep clinical decision support systems fresh. Use these webhooks to trigger downstream audit workflows and ensure immediate data synchronization.

This comprehensive guide helps users diagnose and fix common OpenRouter API errors, including authentication failures (401), rate limiting (429), and bad requests (400). It provides a complete reference table, detailed root causes, and executable code examples in Bash and Python to ensure stable API integration and robust error handling.

This guide provides a comprehensive quickstart for integrating with OpenRouter, a unified endpoint for accessing multiple large language models (LLMs). It includes examples in cURL, Python, and TypeScript, demonstrating how to send chat completion requests, handle complex JSON responses, manage model parameters, and calculate usage cost across various providers (e.g., Llama, GPT-4o, Claude). Ideal for developers testing API connectivity or building multi-model applications.

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.

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.

This guide provides minimal working examples demonstrating the three core PostHog functionalities: event capture, user identification, and feature flag evaluation. It covers both server-side (Node.js, Python) and client-side (JavaScript) SDK usage, as well as direct API calls, making it perfect for initial integration setup, testing, and learning basic product analytics patterns.

Document describes structured prompts, chain-of-thought guidance, few-shot examples, system prompt design, and tooling advice for building reliable prompt engineering workflows in LLM-augmented products.

This skill provides implementation patterns and code examples for creating an incident runbook using Retell AI. It is specifically designed for automating complex workflows, handling emergency notifications, and managing interactive phone calls within a voice agent or telephony system environment.

Provides a comprehensive guide and code examples for configuring Sentry across development, staging, and production environments. It ensures data isolation by using separate DSNs, allows tuning of sample rates (e.g., 10% for production, 100% for dev), and implements environment-specific logic for PII scrubbing and event filtering, optimizing visibility while maintaining data security.

This skill acts as a content freshness specialist, identifying outdated elements—such as statistics, dates, examples, and industry trends—within existing SEO content. It provides strategic guidelines, update priorities (High/Medium/Low), and actionable refresh plans to improve search engine rankings and maintain topical authority. Use it proactively for established but aging content to combat content decay.

This guide provides robust patterns for managing external API rate limits, specifically detailing the implementation of exponential backoff, request queuing, and throttling strategies. It uses TypeScript examples to ensure stable and reliable API interactions. Use this when building production-grade applications that require frequent, high-volume calls to rate-limited services, such as language learning APIs.

This guide provides comprehensive solutions for diagnosing and fixing common technical errors and exceptions encountered when using the TwinMind platform. Whether you are facing API authentication failures, microphone permission issues, transcription timeouts, rate limit exceedances, or audio format incompatibility, this reference offers step-by-step solutions and code examples to ensure smooth operation and successful integration.