Skill UI

This comprehensive guide details multiple strategies for configuring Algolia across distinct environments (development, staging, production). It covers best practices such as index prefixing, scoped API keys, environment variable management, and implementing isolation guards, ensuring data integrity and reliable search functionality in CI/CD pipelines.

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.

This comprehensive guide provides a production-ready reference architecture for implementing scalable search using Algolia. It details best practices for index design (including multi-index strategies), establishing robust data pipelines from source databases, structuring the service layer (search, indexing, settings), and integrating the frontend for optimal performance.

This guide provides production-ready, high-quality patterns for integrating with Algolia Search v5. It covers critical architectural aspects such as implementing singleton client management, performing strongly typed searches, robust error handling (including specific API error codes), efficient batch indexing, and handling multi-tenant environments. Use these patterns to refactor existing code and establish reliable coding standards.

This workflow automates the design handoff process by creating a continuous pipeline from Figma designs to functional React code. It scans Figma components, generates code batches (supporting TypeScript, Tailwind CSS, etc.), and includes change detection to automatically update the codebase when the design source changes. Ideal for building complex design systems and implementing CI/CD design-to-code workflows.

This skill guides the deployment of the Anima design-to-code service as a backend API endpoint. It is essential for building microservices that convert Figma designs into functional code, suitable for internal design tools or production APIs. Supports deployment via Vercel and Google Cloud Run.

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 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.

A comprehensive skill providing patterns for implementing data privacy, PII redaction, and robust audit logging when interacting with large language models like Claude. Use this when your application handles sensitive user data, requiring compliance with regulations such as GDPR or CCPA, ensuring all API calls are secure and auditable.

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.