Skill UI

A comprehensive guide and setup for establishing a fast, reproducible local development loop for web scraping projects using Bright Data. It includes configuring proxy modules, implementing response caching to save credits, and setting up mocked test suites (using Vitest) for robust, isolated testing without requiring live proxy access or consuming resources.

A comprehensive guide to reducing Algolia operational costs. This guide details the pricing structure based on search requests and records, providing advanced techniques such as implementing virtual replicas instead of standard replicas, utilizing multi-query search for request batching, and implementing client-side caching. It also includes strategies for auditing, cleaning up unused indices, and monitoring usage via the Analytics API.

A suite of utilities designed to significantly boost Anima code generation performance. It implements file-based caching with Time-To-Live (TTL) management, enables incremental updates by tracking only changed Figma components, and optimizes output size by cleaning up comments and excess whitespace. Ideal for optimizing large batch generations or speeding up production build pipelines.

This guide addresses the performance degradation when automating Apple Notes, especially with large note collections (10,000+). It details architectural patterns, caching strategies, and scripting best practices (like batch processing and incremental sync) to prevent bottlenecks caused by excessive IPC calls, ensuring automation remains responsive at scale.

This comprehensive guide outlines advanced strategies for optimizing interactions with the Attio REST API. Techniques covered include implementing LRU caching for schemas, using batch queries to avoid N+1 problems, efficient pagination (including streaming), and optimizing connection pooling via keep-alive. It helps developers maximize API throughput, minimize latency, and reliably process large volumes of data.

This guide implements production-grade reliability patterns for integrating with external APIs, specifically Adobe services. It demonstrates how to use circuit breakers to prevent cascading failures, implement graceful degradation with cached fallbacks, and utilize dead letter queues (DLQ) for reliable asynchronous job handling. It ensures your application maintains high availability even when external services are unstable or rate-limited.

A comprehensive guide to production-ready patterns for integrating with Adobe services (Firefly, PDF, etc.). This includes robust authentication with token caching, typed API wrappers with advanced error classification, exponential backoff retry mechanisms, and job polling for asynchronous tasks. Essential for building reliable and maintainable Adobe API integrations in TypeScript or Python.

A comprehensive guide to optimizing Alchemy API usage costs. Learn how to manage Compute Units (CU) by implementing aggressive caching, utilizing batch operations, and selecting the right development plan (Free, Growth, Scale). This tool helps developers monitor usage and reduce API billing expenses for dApps.

A comprehensive, multi-chain reference architecture for building robust decentralized applications (dApps) powered by Alchemy. This guide outlines the full stack, from the React/Next.js frontend and API layer to core blockchain interactions, incorporating best practices like rate limiting, caching, and secure API proxying. Ideal for planning complex, production-grade Web3 systems across multiple chains (ETH, Polygon, etc.).

A comprehensive guide to production-ready patterns for Web3 development using the Alchemy SDK. Covers essential architectural components such as multi-chain client factories, response caching mechanisms, type-safe NFT query builders, and robust error classification, ensuring highly scalable and reliable blockchain applications.

This skill provides a comprehensive guide to instrumenting Algolia search services for enterprise-grade observability. It integrates core monitoring patterns, including Prometheus metrics (latency, error rates, request counts), OpenTelemetry distributed tracing, and structured logging. Use this to achieve deep insights into search performance, user experience, and system health in production environments.

This skill provides a comprehensive guide to optimizing Algolia search performance. It covers best practices for reducing record size, selecting optimal searchable attributes, tuning faceting, implementing client-side caching, and configuring replica strategies. Use this guide to minimize search latency and drastically improve the end-user search experience.