Skill UI

This guide demonstrates how to implement robust Role-Based Access Control (RBAC) for Algolia Enterprise environments. It covers defining granular permissions using ACLs, generating Secured API Keys for strict multi-tenant data isolation, and building middleware to validate service permissions, ensuring the principle of least privilege in large-scale applications.

This skill provides actionable strategies and code patterns to significantly reduce Anima API costs. It focuses on optimizing usage through generation caching, detecting component changes for incremental generation, and implementing smart policies to minimize unnecessary API calls. Ideal for managing large-scale design-to-code workflows and controlling API budget.

This guide provides a reference architecture for automating the design-to-code workflow. It outlines the complete pipeline—from Figma design input to structured React/Vue output—detailing components like Figma API integration, code generation, and crucial post-processing steps (token mapping, normalization). Ideal for establishing scalable design systems and managing large-scale design handoffs in a professional environment.

A guide detailing four validated architectural patterns for integrating Claude APIs, catering to diverse scale and use cases. Choose between Serverless, Streaming Microservice, Queue-Based Pipelines, or complex Orchestrators to optimize performance, cost, and latency for your application, whether it's a real-time chatbot or large-scale batch processing.

This guide provides comprehensive strategies to significantly reduce spending on the Anthropic Claude API. Key techniques include model routing (selecting the most cost-effective model for the task), prompt caching for repeated prompts, using Message Batches for asynchronous tasks, and implementing real-time spend tracking and budget alerts. Essential for managing large-scale, high-cost AI deployments and optimizing cloud LLM expenditures.

This guide provides a set of production-grade TypeScript patterns for robust interaction with the Attio REST API. It covers essential best practices including typed clients, automatic retry mechanisms with exponential backoff, cursor-based pagination iterators, and multi-tenant factory implementation, ensuring reliable and scalable API integration. Use these patterns to handle common API challenges like rate limiting and large datasets efficiently.

This comprehensive guide details advanced techniques for optimizing Bright Data API scraping performance. It covers implementing connection pooling, robust response caching layers (LRU Cache), and managing concurrent requests with backpressure control. Use this when facing slow API responses or requiring high-throughput, scalable data extraction.

A comprehensive guide detailing three validated architectural patterns (Monolith, Service Layer, Microservice) for integrating with the Canva Connect API. This blueprint helps developers choose the optimal structure—from simple MVPs to complex enterprise systems—by addressing concerns like token management, asynchronous exports, rate limiting, and scaling strategies.

This tool provides comprehensive load testing, auto-scaling simulation, and capacity planning for Canva Connect API integrations. It is essential for performance testing, managing complex rate limits (both per-user and global), and ensuring robust, scalable production workloads for Canva-dependent applications.

A comprehensive guide detailing how to securely configure and manage Canva Connect API integrations across development, staging, and production environments. This resource covers environment strategy, best practices for OAuth credential management, secret handling (AWS, GCP, Vault), and implementing environment isolation guards to ensure secure and scalable deployments.

Automate the deployment of CAST AI across various multi-cloud Kubernetes clusters, including EKS, GKE, and AKS. This module uses Terraform Infrastructure as Code (IaC) patterns to reliably configure necessary components like IAM roles, node autoscaling policies, and cluster resources, ensuring standardized onboarding across different cloud environments.

A comprehensive guide to optimizing CAST AI's core performance metrics, including node provisioning speed, autoscaler responsiveness, and API call efficiency. This skill covers techniques like configuring headroom, selecting optimal instance families, tuning evictors, and implementing caching for multi-cluster dashboards to ensure high availability and cost efficiency in cloud environments.