Skill UI

This advanced workflow allows developers to clone live websites directly into structured React or HTML code using the Anima platform. It goes beyond simple cloning by featuring post-generation customization rules (e.g., updating utility classes or imports) and a dedicated design token mapper. This ensures the generated code is immediately usable and adheres strictly to the project's existing design system tokens, while also organizing the final component structure.

This guide details how to install and configure the Anima SDK for robust Figma-to-code generation. It is essential for developers setting up design-to-code automation pipelines, requiring configuration of both Anima and Figma API tokens. The SDK enables converting designs into production-ready React, Vue, or HTML components with Tailwind, MUI, or AntD styling.

This utility provides robust methods to manage API rate limits when integrating with the Anima API. It implements throttling using the `Bottleneck` pattern for stable, high-volume operations, and includes a 429 retry handler with progressive backoff. This is essential for large-scale batch generation of design systems or complex component libraries.

This guide details production-ready patterns for integrating the Anima SDK into automated design-to-code pipelines. It covers best practices such as implementing a singleton client, managing generation cache, normalizing output for project conventions (e.g., TSX structure, utility classes), and incorporating retry logic for API resilience. Use it when building robust, reusable Anima client wrappers for enterprise applications.

This guide outlines critical security best practices for design-to-code pipelines using Anima and Figma. It covers securing API credentials by restricting token scopes (e.g., read-only access for Figma), enforcing server-side execution for SDKs, and implementing robust secret management using cloud services like GCP Secret Manager. This minimizes the risk of credential leakage in CI/CD environments.

This skill guides the secure deployment of Claude API integrations into production cloud environments. It provides comprehensive instructions for implementing services across multiple infrastructures, including Docker, GCP Cloud Run, and Kubernetes. The guide covers best practices such as secret management, health checks, and reliable rollback procedures to ensure high service reliability.

This module provides structured implementations of critical reliability patterns (Circuit Breaker, Graceful Degradation, Idempotency) for integrating with the Claude API. It helps developers build resilient, production-grade applications that can handle transient failures, rate limits, and service outages without failing completely, significantly enhancing system stability and user experience.

This resource provides production-ready architectural patterns for integrating Anthropic's Claude models using TypeScript and Python. It covers robust client wrappers, managing multi-turn conversations, enforcing structured JSON output via prefilling, and implementing multi-tenant architectures. Essential for building reliable, enterprise-grade AI applications.

A comprehensive guide detailing how to upgrade Anthropic SDKs (Python/TypeScript) and manage API version transitions. Learn to migrate from Text Completions to the Messages API, incorporate new features like tool use, and handle common breaking changes across major SDK versions.

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.

A comprehensive guide on managing rate limits when interacting with the Apify Platform API. It details best practices for building robust, high-throughput automation workflows, covering built-in retries, request queuing using p-queue, batching large payloads, and staggering concurrent operations to prevent 429 errors and maintain system stability.

A comprehensive guide to building robust, production-ready applications using the Apify SDK and apify-client in TypeScript. Covers advanced topics like standardized client singleton patterns, selecting the right Crawlee crawler (Cheerio, Playwright, Puppeteer), implementing robust Actor lifecycles, and managing dataset/key-value store operations.