Skill UI

This comprehensive skill guides developers on implementing full observability for HubSpot API integrations. It details how to instrument calls using industry-standard tools, including Prometheus metrics (Counters, Histograms, Gauges), OpenTelemetry tracing, structured logging (pino), and configuring AlertManager rules. Use this when needing to monitor CRM integration health, track latency, detect errors, or manage rate limits for mission-critical API operations.

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.

This guide provides advanced patterns for managing API rate limits, crucial for reliable integration with platforms like HubSpot. It covers implementing exponential backoff, honoring 'Retry-After' headers, using request queuing (throttling), and optimizing throughput through batch operations to gracefully handle 429 rate limit errors.

This collection provides production-ready, idiomatic patterns for the @hubspot/api-client SDK, specifically tailored for TypeScript. It addresses critical development concerns including creating typed wrappers, implementing robust, structured error classification (handling rate limits, authentication issues, etc.), and managing efficient batch operations (create, read, upsert) for HubSpot CRM data. Use this when building scalable, reliable, and maintainable HubSpot integrations.

A comprehensive guide for developers migrating the intercom-client npm package, particularly addressing major version jumps (e.g., v5 to v6) and associated breaking changes. Learn how to update client initialization, modify contact and conversation operations, and handle API version pinning using TypeScript and modern asynchronous patterns.

Provides advanced strategies for managing API rate limits when integrating with Klaviyo. This skill implements robust patterns like exponential backoff, respecting `Retry-After` headers, and utilizing request queuing. It ensures stable, high-throughput data synchronization, preventing 429 errors during large-scale bulk operations.

This comprehensive skill guides users through the entire Fluid storage extension lifecycle within KubeSphere. It allows for installing, upgrading, and uninstalling the Fluid extension, and managing various data resources. Users can generate YAML manifests for Datasets and specialized runtimes (Alluxio, JuiceFS, Thin), perform data loading/cache warming, scale operations, and troubleshoot issues using both kubectl and KubeSphere APIs.

This guide provides comprehensive strategies and code examples for managing and reducing API costs associated with large-scale usage of Lucidchart. It covers optimizing document exports through caching, batching operations, reducing excessive real-time collaboration events, and efficiently managing user seats to ensure cost-effective diagramming workflows.

This utility provides a local, mock development loop for integrating and testing the Lucidchart diagramming API. It simulates document, page, and shape data, allowing developers to build and validate diagram automation tools (CRUD operations) without needing a live Lucid account. This enables fast iteration and robust debugging in a controlled sandbox environment.

This guide provides advanced techniques for optimizing API interactions with Lucidchart, especially when dealing with enterprise diagrams containing thousands of shapes. Key strategies include implementing Redis caching for metadata, utilizing cursor-based pagination for list retrieval, grouping updates for batch operations, and robust rate limit handling with exponential backoff. It ensures stable and high-throughput integration.

This guide provides a comprehensive overview of the rate limits imposed by the MindTickle API across various endpoints, such as user management, content upload, and quiz result exports. It details specific limits for different operations and provides robust engineering solutions using TypeScript. Key implementation strategies include implementing a token-bucket rate limiter, developing a retry mechanism with exponential backoff, and optimizing bulk data processing through batching to ensure stable and efficient application integration.

This comprehensive workflow provides full Create, Read, Update, and Delete (CRUD) capabilities for managing Miro boards and all embedded items. Users can programmatically manage entire boards, sticky notes, shapes, cards, frames, and tags using the official REST API v2. Ideal for integrating Miro into automated workflows, automating retrospective reports, or building complex collaboration tools that require structured board content manipulation.