Skill UI

A comprehensive guide providing minimal working examples for core Cohere API v2 endpoints, including Chat completion, text embedding, and search reranking. This resource details basic setup, usage patterns, and includes runnable code examples in both TypeScript and Python, making it perfect for new AI integrations or learning advanced LLM functionality.

Provides production-ready client patterns for interacting with the Fathom API, implemented in both Python and TypeScript. This SDK wrapper is designed for building reusable client services, implementing robust meeting data pipelines, or integrating Fathom's core features (like transcripts and summaries) into specialized applications.

A comprehensive guide to the three primary architecture patterns for integrating with Figma: CLI scripts, Webhook services, and dedicated plugins. This resource helps developers select the optimal pattern (REST vs. Plugin API) based on whether the use case requires real-time event handling, local automation, or in-editor component interaction. Ideal for planning robust Figma-connected applications like design token synchronization or linting.

This comprehensive guide details the ten most common mistakes and anti-patterns encountered when integrating with the Figma REST and Plugin APIs. It covers critical topics such as preventing oversized data fetches, managing rate limits, securing tokens, handling color format conversions, and optimizing data sync using webhooks instead of polling. Essential for code reviews and onboarding. Use when reviewing Figma code, onboarding new developers, or auditing an existing Figma integration.

A collection of production-ready patterns for interacting with the Figma REST API and Plugin API. It provides type safety, robust error handling, and reusable abstractions for tasks like building client wrappers, extracting design tokens, and traversing complex node trees. Essential for building scalable, enterprise-grade Figma integrations.

This guide provides a minimal working example for integrating with the Flexport REST API v2. It demonstrates core logistics operations, including listing shipments, retrieving detailed shipment milestones, and listing associated containers. It is ideal for developers starting a new Flexport integration, testing API connectivity, or learning the basic API patterns.

Provides robust patterns for handling API rate limits, throttling, and connection errors when integrating with the Framer API. It covers implementing exponential backoff, retry mechanisms, batching large CMS writes, and debouncing plugin operations to ensure reliable and high-throughput API calls.

This skill provides a comprehensive guide for analyzing, planning, and executing upgrades of the Framer SDK, plugin API, and migrating between different Framer platform versions. It helps developers detect breaking changes, follow version checks, and manage common migration patterns required when updating the Framer environment.

A collection of production-ready patterns for integrating frontend applications with backend APIs. It solves complex asynchronous issues such as race conditions, stale data, and duplicate requests. Patterns include centralized API layering, request cancellation (AbortController), exponential backoff retries, debouncing, and request deduplication, ensuring highly resilient and reliable user experiences.

This module provides production-ready patterns for interacting with the Glean enterprise search API. It features a typed client, implementing singleton patterns and robust mechanisms for search and indexing. Key patterns include batch pagination, comprehensive error handling (e.g., retries for rate limits), and a fluent request builder for executing complex, reliable API calls.

This comprehensive checklist guides developers through the necessary steps to deploy a robust and reliable Grammarly API integration in a production environment. It covers critical aspects such as secure credential storage, rate limit handling, implementing text chunking, designing error resilience patterns (circuit breakers, retries), and establishing comprehensive monitoring and alerting systems to ensure high content quality and system uptime.

This guide provides production-ready patterns for integrating with the Grammarly API using both TypeScript and Python. It covers essential architectural aspects, including typed client implementation, robust token management (OAuth flow), and efficient text chunking for processing large documents. Use this when building scalable, reliable Grammarly-powered features into your application.