Skill UI

This comprehensive guide details how to implement robust webhook endpoints for CodeRabbit, an AI-powered code review tool. It covers essential security practices, including signature validation (HMAC-SHA256), and provides structured methods for handling various event types (e.g., PR reviews, check run completions, comments). Use this skill when integrating CodeRabbit into CI/CD pipelines to automate notifications, track metrics, and enforce quality gates.

Provides comprehensive observability patterns for Firecrawl web scraping operations. It covers key metrics such as scrape success rates, credit consumption tracking, content quality assessment, and latency monitoring. Use this skill for implementing robust monitoring dashboards, setting up proactive failure alerts, and optimizing the reliability of web crawling workflows.

A comprehensive toolkit for monitoring the health and performance of Fireflies.ai integration. It tracks crucial metrics such as API connectivity, webhook delivery status, transcript processing latency, and seat utilization. Built using Prometheus metrics and suitable for Grafana dashboards, ensuring reliable data pipeline monitoring for engineering teams.

This skill collects a comprehensive debug bundle from the Instantly workspace. It gathers critical metrics including campaign state, account health, warmup analytics, webhooks, and background job status. The resulting structured JSON report is ideal for creating detailed support tickets, performing technical troubleshooting, or conducting internal system audits.

Comprehensive monitoring and alerting for Instantly.ai integrations. This skill tracks critical campaign metrics (bounce rate, open rate, reply rate), monitors account warmup status, and tracks webhook delivery performance. It ensures real-time visibility into campaign health and deliverability issues.

This skill aggregates public sentiment and discussion about any given topic from the last 30 days. It pulls comprehensive data and engagement metrics from major sources including Reddit, X, YouTube, TikTok, Hacker News, and general web sources. It is invaluable for market research, competitive analysis, or understanding rapidly changing cultural and technological trends.

This guide details how to implement comprehensive observability for AI agents. It covers monitoring key metrics such as task success rates, step failures, execution duration, and credit consumption. Use this when setting up performance dashboards, configuring real-time alerts (via webhooks/Prometheus), or tracking agent reliability over time.

A comprehensive guide and implementation using TypeScript to establish production-grade observability for Linear API integrations. This includes defining Prometheus metrics (tracking latency, error rates, rate limits, and webhooks), implementing structured logging (using pino), and setting up robust health check endpoints. It ensures full visibility into API performance and system health, critical for mission-critical SaaS applications.

This skill provides a comprehensive guide to setting up full observability for Lokalise integrations. It covers crucial metrics, traces, and alert configurations, monitoring everything from API response times and rate limit consumption to translation progress and webhook reliability. Ideal for developers building robust monitoring dashboards and alerting systems for localization workflows.

Helps developers systematically optimize web performance by measuring key metrics, reducing bundle size, deferring scripts, optimizing images and fonts, and tuning caching and CSS for faster Time to Interactive and better Lighthouse scores.

This tool provides a comprehensive deep dive into a single webpage's SEO health. It evaluates on-page elements, content quality metrics, technical metadata (Open Graph, Schema, etc.), image optimization, and Core Web Vitals potential issues. Use this when you need to thoroughly audit a URL for search engine optimization compliance and actionable improvements.

A comprehensive guide to using k6 for robust performance and load testing across APIs, WebSockets, and browser scenarios. Learn to write realistic load simulations (smoke, load, stress, soak), analyze performance metrics, set SLAs, and integrate testing into CI/CD pipelines to ensure system reliability before deployment.