Skill UI

A comprehensive guide for developing and managing applications using Amazon Aurora DSQL, a serverless, PostgreSQL-compatible distributed SQL database. This skill covers core capabilities including direct query execution, robust schema management, safe data migration from MySQL, multi-tenant architectural patterns, IAM-based authentication, and detailed query plan explainability for performance tuning. Essential for developers handling complex database evolution.

This module provides production-ready, type-safe patterns for interacting with the BambooHR REST API, supporting TypeScript and Python. It wraps raw HTTP calls into robust, retry-aware clients, handling complex tasks like error management and multi-tenancy. Use this when building reliable, enterprise-grade integrations with BambooHR.

This technical guide provides patterns for handling rate limits, throttling, and concurrency issues when scraping data using Bright Data services. It demonstrates implementing concurrency control using queuing, applying exponential backoff for transient errors (like 429 or 503), and managing specific API trigger rate limits (e.g., 20/min, 60/hr). Essential for building robust, large-scale web scrapers.

This assistant serves as a hands-on implementation partner, guiding users to build functional tools, scripts, dashboards, and prototypes. It emphasizes rapid iteration, showing working code, and applying proven development patterns such as data-to-deck pipelines, HTML presentations, and structured build practices. Use it when the goal is to transform analysis or concepts into tangible, working software or robust automation.

This guide provides advanced patterns for managing rate limits when integrating with the Canva Connect API. It covers implementing exponential backoff with jitter for retries, using queue-based throttling to control request throughput, and building proactive rate limit trackers. Ideal for building stable, production-grade integrations that must handle 429 errors and quotas gracefully.

A comprehensive guide to implementing production-grade reliability patterns for the Canva Connect API. Learn to use Circuit Breakers, graceful degradation, exponential backoff retries, and token refresh strategies to build fault-tolerant integrations that can handle network failures, rate limits, and service outages gracefully.

This guide provides essential best practices for building resilient applications that interact with rate-limited APIs, specifically addressing the CAST AI REST API. It details the implementation of exponential backoff with jitter and utilizing request queuing mechanisms (like p-queue) to gracefully handle HTTP 429 errors. Use this pattern to optimize API call patterns and ensure system stability when making batch or frequent requests.

Provides a comprehensive, production-ready reference architecture for building advanced analytics platforms powered by ClickHouse. It details everything from project layout (TypeScript/Node.js structure) and data ingestion pipelines (Kafka, Webhooks) to the optimal 3-layer schema design (Raw, Hourly, Daily) and multi-tenancy patterns, ensuring scalable and efficient OLAP query performance.

This guide provides production-ready patterns for using the @clickhouse/client library in Node.js. It covers critical, real-world scenarios such as safe typed queries, streaming large data inserts (with backpressure handling), robust batch operations with retries, and streaming SELECT queries for low memory consumption. It also includes best practices for comprehensive error handling and connection lifecycle management, ensuring stable and scalable ClickHouse integrations for data pipelines.

Provides comprehensive strategies for handling external API rate limits (HTTP 429 errors). This skill implements advanced patterns including exponential backoff with jitter, request queuing, and header monitoring. It is crucial for building reliable, high-throughput integrations with rate-limited services like ClickUp.

A comprehensive guide to securing ClickUp API usage. Learn best practices for managing API tokens, implementing least-privilege access, and auditing usage patterns. This includes secure token rotation procedures, using environment variables, setting up pre-commit hooks to prevent leaks, and structuring calls for robust audit logging.

This guide details advanced patterns for managing API rate limits, particularly for external AI services like Cohere. It covers implementing exponential backoff with jitter for handling transient 429 errors, utilizing concurrency-limited request queues, and building proactive rate limit trackers. These techniques ensure highly reliable and optimized API throughput in production systems.