Skill UI

This comprehensive guide teaches developers how to build advanced, interactive, and data-driven components within Framer using React. It covers creating components with dynamic property controls (e.g., animated counters), integrating real-time data from external APIs, and implementing sophisticated behavioral code overrides (such as scroll-triggered animations or magnetic interactions). Ideal for extending Framer's capabilities for professional web design.

This comprehensive 'Hello World' guide serves as a foundational tutorial for Framer development. It demonstrates key skills across the ecosystem, including building functional plugins (UI interaction), creating customizable code components with property controls, implementing dynamic code overrides for sophisticated animations, and interacting with the Framer Server API for headless site data management. Ideal for developers starting a new Framer integration or mastering core API patterns.

A comprehensive guide to production-ready, robust coding patterns for Framer development. This resource covers key areas including type-safe CMS interactions, plugin state management hooks, reusable component architectures, and server API wrappers. Use this when refactoring existing SDK usage or establishing scalable coding standards for complex Framer integrations.

A comprehensive guide to implementing real-time data synchronization and handling event triggers with Framer's API. This skill covers subscribing to CMS changes via WebSockets, implementing secure external webhook endpoints with signature validation, and integrating Framer plugin event listeners for dynamic interaction. Use this when building complex, event-driven web applications connected to Framer.

This guide provides techniques to optimize Grammarly API interactions, focusing on reducing latency and improving throughput. Learn how to implement efficient caching strategies (like LRU cache) for repeated score checks and how to execute multiple API calls in parallel using Promise.all. Use this when experiencing slow response times or needing cost/performance improvements in Grammarly integrations.

A comprehensive guide and implementation pattern for handling rate limits, backoff, and idempotency when integrating with the Grammarly Text API. It provides a custom rate limiter and robust retry logic to manage API throughput, ensuring reliable processing of high volumes of documents and stable interaction with various endpoints (e.g., writing score, plagiarism checks).

This skill provides advanced techniques to optimize interactions with the Hootsuite API. It addresses common performance bottlenecks by implementing efficient LRU caching for social profiles, optimizing message scheduling through concurrent batch processing, and ensuring robust connection reuse. Use this when experiencing slow API responses or needing to process high volumes of automation tasks efficiently.

A comprehensive guide for diagnosing and fixing common HubSpot API errors (e.g., 401, 403, 429, 400). It provides real error response bodies, root cause analysis, and actionable code solutions for debugging failed API requests, improving integration reliability, and managing complex CRM interactions.

Master advanced techniques for optimizing API interactions with HubSpot. Learn to implement batch operations, utilize effective caching strategies (e.g., LRU), minimize property requests, and handle large datasets via efficient pagination and streaming. This skill dramatically improves throughput and reduces API call latency across CRM operations.

A comprehensive guide to setting up a robust and efficient local development environment for Intercom integrations. This workflow emphasizes test isolation, utilizing mock clients (e.g., vitest) for reliable unit testing, proper environment variable management, and simulating real-world interactions via webhook tunneling (ngrok). It ensures fast iteration cycles when developing SaaS features against the Intercom API.

A comprehensive guide for optimizing Intercom API interactions. It covers advanced strategies such as implementing response caching (LRUCache), designing efficient search queries, handling large datasets with cursor-based pagination, managing connection pooling, and executing rate-aware parallel requests. Essential for developers building high-throughput, low-latency Intercom integrations.

This module provides robust coding patterns for interacting with the Linktree API, specifically designed to prevent hitting rate limits (429 errors). It implements a token bucket rate limiter and a sophisticated retry strategy featuring exponential backoff and jitter. Ideal for use cases involving bulk link updates, scheduled analytics data fetching, or high-volume data synchronization across multiple accounts, ensuring reliable API interaction.