Skill UI

A comprehensive guide for diagnosing and resolving common errors encountered when integrating with the Figma REST API or Figma Plugin API. It covers status codes (403, 429, 404), token management, rate limiting, and plugin-specific runtime issues, ensuring robust and stable API development.

A comprehensive diagnostic tool designed to collect all necessary evidence for troubleshooting persistent Figma REST API issues or preparing detailed support tickets. It automatically tests connectivity, checks rate limit status, captures environment information, and redacts sensitive data, providing a clean, actionable archive for developers and QA teams.

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.

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.

Provides advanced best practices for optimizing Glean's enterprise search performance and scalability. Covers critical techniques such as implementing effective batch sizing, caching strategies, connection pooling, and robust rate limit management to significantly reduce search latency and maintain high-throughput indexing for massive, diverse datasets.

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.

A comprehensive utility designed to collect all necessary diagnostic evidence for troubleshooting HubSpot API issues and preparing detailed support tickets. It gathers runtime environment details, SDK versions, API connectivity checks, rate limit information, and redacts application logs, providing a holistic view for technical support teams.

This guide provides a quick reference for diagnosing and fixing common errors encountered when using the Intercom API. It details specific HTTP status codes (e.g., 401, 404, 429), their root causes, and actionable solutions, including code snippets for secure API interaction and implementing backoff logic for rate limiting. Essential for developers troubleshooting integration failures.

This script gathers comprehensive diagnostic evidence for troubleshooting Intercom integrations. It systematically checks API authentication status, rate limits, platform status, SDK versions, and collects redacted logs. Use this utility when encountering persistent bugs or preparing detailed technical support tickets for Intercom support.

Automatically collects comprehensive diagnostic evidence for Klaviyo support tickets. This tool gathers environment details, SDK versions, API connectivity test results, rate limit headers, and recent application logs, ensuring support teams have all necessary data for efficient troubleshooting of persistent marketing automation issues.

This comprehensive guide details techniques for optimizing Linktree API integrations in high-traffic, volatile environments. It covers implementing Redis caching strategies, managing rate limits with exponential backoff, and optimizing batch operations and connection pooling to ensure data freshness, reliability, and cost efficiency.