Skill UI

This comprehensive guide provides advanced strategies for optimizing interactions with the Klaviyo API. It covers implementing response caching (LRU Cache), efficient cursor-based pagination, request batching using DataLoader, and controlling API concurrency. Use this when dealing with slow API responses, large datasets, or high-throughput integration requirements.

This skill provides comprehensive guidance on optimizing operational costs on the Apify platform. It covers analyzing Compute Units (CU) usage, managing proxy consumption (residential vs. datacenter), and optimizing scraping logic (memory, concurrency) to ensure efficient and cost-effective web scraping workflows.

This comprehensive guide details how to optimize Apify Actors for maximum efficiency, cost-effectiveness, and reliability. Learn to select the appropriate crawler (e.g., Cheerio, Playwright), tune concurrency limits, manage memory consumption, and implement robust proxy rotation strategies for diverse web scraping workloads, ensuring your scraping tasks are fast and stable.

This skill provides comprehensive solutions for managing rate limits and throttling when interacting with the AssemblyAI Speech-to-Text API. It implements advanced patterns like exponential backoff with jitter, queue-based concurrency control, and resilient streaming retry logic. Use it when building high-throughput, reliable applications that process large volumes of audio data.

This technical guide provides patterns for handling rate limits, throttling, and concurrency issues when scraping data using Bright Data services. It demonstrates implementing concurrency control using queuing, applying exponential backoff for transient errors (like 429 or 503), and managing specific API trigger rate limits (e.g., 20/min, 60/hr). Essential for building robust, large-scale web scrapers.

This skill provides advanced strategies for optimizing Canva Connect API performance. It covers implementing robust caching mechanisms (in-memory and Redis) to reduce redundant calls, handling pagination using continuation tokens, and implementing smart polling with progressive backoff for asynchronous operations like exports. It also details connection pooling and concurrency management to maximize request throughput and minimize latency for stable Canva integrations.

This guide details advanced patterns for managing API rate limits, particularly for external AI services like Cohere. It covers implementing exponential backoff with jitter for handling transient 429 errors, utilizing concurrency-limited request queues, and building proactive rate limit trackers. These techniques ensure highly reliable and optimized API throughput in production systems.

This skill provides methods for managing GPU quota limits and rate restrictions for CoreWeave cloud services. It includes using `kubectl` to check resource quotas and demonstrates implementing robust request queuing mechanisms using Python's `asyncio` library, ensuring stable and efficient resource allocation for high-concurrency inference endpoints.

A comprehensive guide to production-ready patterns for ElevenLabs' TypeScript and Python SDKs. This resource covers crucial best practices including singleton client implementation, type-safe TTS service wrappers, robust error classification (rate limiting, quota), and concurrency management using request queues. Essential for building scalable and reliable voice AI applications.

This skill provides comprehensive strategies for managing rate limits when interacting with the Figma REST API. It implements crucial patterns like exponential backoff, respects 'Retry-After' headers, utilizes request queuing with concurrency control, and includes a proactive rate limit monitor. Use this when developing high-volume, resilient integrations that frequently encounter 429 errors or require optimized API throughput.

A comprehensive checklist designed to harden Linktree API integrations for high-concurrency, production-grade reliability. It covers critical aspects including secure secrets management, rate limit handling, robust error resilience (circuit breakers, exponential backoff), comprehensive monitoring setup, and advanced security practices like webhook signature verification. Use this guide to ensure link-in-bio analytics remain accurate and system uptime is maximized under viral traffic loads.

A comprehensive set of structured patterns for integrating with the Lucidchart REST API. These patterns handle complex requirements such as OAuth 2.0 token lifecycle management, mandatory API version negotiation, deep shape tree structures, and robust error handling for concurrency issues (e.g., document locking, rate limiting). Includes utilities for building type-safe queries and mocking test scenarios.