Skill UI

This skill provides advanced methods for load testing and scaling web scraping pipelines using Firecrawl. It manages rate limits and optimizes throughput by implementing concurrency control, batch processing, and queue-based request throttling. Essential for capacity planning, stress-testing scraping performance, or maximizing data ingestion efficiency across various service plans.

This guide provides production-ready patterns for integrating the Firecrawl SDK in TypeScript and Python. It covers essential architectural best practices, such as implementing singleton clients, typed service wrappers, automatic retries with exponential backoff, concurrency management, and robust response validation using Zod. Ideal for building scalable, reliable web scraping services.

A comprehensive guide to production-grade concurrency patterns in Go. It details the proper use of goroutines, channels, sync primitives, and context management. Use this skill when building highly concurrent applications, implementing worker pools, managing goroutine lifecycles, or debugging race conditions in Go.

Curated guidelines covering idiomatic Go error handling, interface design, concurrency patterns, context propagation, testing, and module management for reliable team codebases.

Collection of Go idioms and best practices for building robust, maintainable services, covering simplicity, zero values, interface returns, error handling, and concurrency when writing, reviewing, or refactoring Go code.

A specialized AI assistant acting as an expert Haskell engineer. This skill focuses on advanced type systems (GADTs, type families), pure functional architecture, concurrency (STM, async), and high-assurance software design. Use it for building robust, idiomatic, and maintainable Haskell code.

This skill guide provides advanced techniques for optimizing Ideogram API usage. It covers selecting optimal model tiers (e.g., Turbo vs. Standard) based on desired quality and speed, implementing prompt-based caching to reduce API calls and costs, and managing parallel generation with concurrency limits for high throughput. Additionally, it demonstrates CDN integration for rapid asset delivery.

Provides comprehensive patterns for managing API rate limits and handling throttling when interacting with services like Ideogram. This guide demonstrates robust techniques including implementing exponential backoff with jitter, utilizing concurrency-limited queues (e.g., p-queue), and implementing token bucket algorithms. Use this skill to ensure stable, high-throughput, and reliable batch API calls.

This guide provides advanced techniques for optimizing API integrations, specifically for handling high-volume data operations and rate limits. It covers implementing robust caching strategies for analytics data, managing lead inputs via controlled batching and concurrency, and utilizing prefetching for efficient pagination. It also demonstrates connection pooling using keep-alive mechanisms to maximize throughput and minimize latency.

This skill provides robust patterns for handling API rate limits (e.g., 429 errors) when building high-throughput integrations. It demonstrates best practices including exponential backoff with jitter, request queuing, concurrency control, and specific endpoint throttling mechanisms, ensuring reliable service connectivity.

This skill provides comprehensive strategies for managing API rate limits, focusing on high-volume and mission-critical workflows. It implements exponential backoff with jitter, task concurrency limiting using `asyncio`, and request queue patterns. Designed to detect and gracefully handle `429 Too Many Requests` errors, ensuring reliable and stable execution even under severe throttling conditions.

A comprehensive guide to mastering asynchronous programming using Kotlin Coroutines and Flow. Covers advanced topics such as structured concurrency, robust exception handling, and creating reactive data streams with StateFlow and SharedFlow. Essential for developing high-performance, modern Kotlin applications.