Skill UI

This guide provides best practices for optimizing HubSpot integration costs and performance. Learn to manage API call volume by implementing batch reads, using server-side search filters, and leveraging webhooks instead of continuous polling. It covers crucial concepts like rate limit monitoring and caching to prevent 'Too Many Requests' errors (429), ensuring stable and cost-effective development.

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.

A comprehensive checklist and guide for securely deploying HubSpot CRM integrations to a production environment. It covers mandatory pre-deployment verification steps (like token scoping and secure storage), implementing robust health check endpoints, configuring critical monitoring alerts (rate limits, 401/429 errors), and executing post-deployment validation scripts to ensure system stability and reliability upon launch.

This skill provides a comprehensive guide to setting up full observability for Intercom integrations. It covers implementing Prometheus metrics (counters, histograms, gauges) to track API request status, latency, and error rates. Furthermore, it demonstrates structured logging using Pino and OpenTelemetry tracing, offering deep, actionable insights into integration health. Ideal for DevOps, backend engineering, and robust system monitoring.

A comprehensive checklist for ensuring Intercom integrations are robust and production-ready. It covers critical areas such as authentication, error handling (rate limits, retries), secure webhook validation, data privacy (PII, GDPR), and monitoring setup. Includes sample TypeScript and Bash scripts for pre-flight verification and graceful rollback procedures.

Provides advanced techniques for handling API rate limits, specifically targeting 429 errors. Implementations cover exponential backoff with jitter, queue-based request throttling, and proactive monitoring of rate limit headers (X-RateLimit-Remaining, X-RateLimit-Reset). Ideal for optimizing API request throughput and ensuring high reliability when integrating with services like Intercom.

A comprehensive checklist designed to harden Linktree API integrations for high-concurrency, production-grade reliability. It covers critical aspects including secure secrets management, rate limit handling, robust error resilience (circuit breakers, exponential backoff), comprehensive monitoring setup, and advanced security practices like webhook signature verification. Use this guide to ensure link-in-bio analytics remain accurate and system uptime is maximized under viral traffic loads.

This guide provides comprehensive strategies for optimizing API usage and managing costs when integrating with Miro. It covers credit monitoring, advanced techniques like caching, server-side filtering, batching, and subscribing to webhooks. By implementing these best practices, developers can drastically reduce API call volume, stay within rate limits, and ensure highly efficient and cost-effective application development.

This skill provides comprehensive deployment scaffolding for Miro REST API v2 integrations. It manages the entire lifecycle, including setting up OAuth 2.0 authentication, handling incoming webhooks, and ensuring continuous health monitoring. It supports deployment across major cloud platforms like Vercel, Fly.io, and Google Cloud Run, simplifying complex multi-environment SaaS application setups.

Provides comprehensive observability for Miro REST API v2 integrations. It captures critical metrics using Prometheus (request rates, latency, error tracking) and OpenTelemetry traces for end-to-end request flow visibility. Includes structured logging for detailed debugging and robust rate limit management, ensuring your applications are highly reliable and maintainable.

This skill implements a comprehensive solution for managing Miro REST API rate limits. It incorporates a credit-based monitoring system, exponential backoff with jitter, and request queuing. This ensures reliable, high-throughput data integration by respecting Miro's usage quotas and handling API throttling (429 errors) gracefully.

This skill provides a comprehensive framework for setting up robust observability for Navan API integrations in production environments. It guides users through implementing structured logging, tracking request latency, classifying various errors (auth, rate limit, server), and monitoring the OAuth token refresh lifecycle. Includes practical steps and YAML examples for configuring alerts and building dashboards in platforms like Datadog, CloudWatch, or Prometheus/Grafana.