Skill UI

This guide provides comprehensive strategies to significantly boost the performance and reliability of applications deployed on Fly.io. Techniques covered include eliminating cold starts (auto-stop/start), right-sizing Virtual Machines based on workload demands, implementing multi-region deployment for low latency, and optimizing connection pooling for databases. Essential for scaling modern SaaS applications.

This tool provides comprehensive observability for enterprise search systems (Glean). It tracks critical metrics such as search latency (p95), zero-result query rates, indexing throughput, and stale content ratios. By monitoring connector sync status and detecting indexing degradation, it allows teams to proactively maintain search relevance and ensure sub-second response times, preventing silent data quality decay.

This document outlines the reference architecture for integrating diverse enterprise knowledge sources (such as Confluence, Jira, Notion, and Slack) into the Glean search index. It details the end-to-end data flow, covering connector frameworks, message queuing, permission synchronization (ACLs), and client-side search APIs. Designed to ensure continuous, reliable, and low-latency unified search across all corporate data.

This utility enables multi-camera streaming by converting standard camera protocols (RTSP, RTMP, HTTP) into low-latency WebRTC streams using the go2rtc sidecar. It is essential for building real-time surveillance dashboards, live video monitoring systems, or integrating diverse IP cameras into a single web interface.

This skill implements comprehensive observability (metrics, logging, and alerting) for Grammarly API integrations. It monitors critical performance indicators such as text check latency (p95), API error rates, suggestion acceptance rates, and token consumption. Use this setup when establishing robust monitoring systems, tracking real-time API performance degradation, or implementing proactive alerting to ensure consistent, high-quality user experiences in writing and editing flows.

This guide provides techniques to optimize Grammarly API interactions, focusing on reducing latency and improving throughput. Learn how to implement efficient caching strategies (like LRU cache) for repeated score checks and how to execute multiple API calls in parallel using Promise.all. Use this when experiencing slow response times or needing cost/performance improvements in Grammarly integrations.

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 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 guide for optimizing Intercom API interactions. It covers advanced strategies such as implementing response caching (LRUCache), designing efficient search queries, handling large datasets with cursor-based pagination, managing connection pooling, and executing rate-aware parallel requests. Essential for developers building high-throughput, low-latency Intercom integrations.

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 guide provides advanced best practices for optimizing interactions with the Miro REST API v2. It covers essential patterns like cursor-based pagination to prevent over-fetching, implementing robust caching strategies (In-Memory/Redis) for reduced latency, and managing connections and concurrency for reliable bulk operations. It is designed for building scalable, high-throughput, and efficient integrations into Miro.