Skill UI

This skill provides a comprehensive guide to configuring event-driven workflows and robust notification systems for Databricks jobs. It covers setting up various notification destinations (Slack, Teams, Email, PagerDuty) and triggering alerts based on job lifecycle events (success, failure, start). Furthermore, it demonstrates advanced monitoring using system audit tables and creating automated SQL alerts for critical data pipeline monitoring.

Master the implementation of Firecrawl webhooks for robust, real-time handling of asynchronous crawling and batch scraping jobs. Instead of inefficiently polling the crawl status, configure webhook endpoints to receive instant POST events (e.g., `crawl.page`, `crawl.completed`). This guide covers event types, signature verification using HMAC-SHA256, and processing streamed data for building advanced data pipelines.

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.

This skill guides you through integrating PostHog's Customer Data Platform (CDP) features. It covers setting up webhooks to trigger real-time actions (e.g., syncing to CRM, sending notifications) when specific user events occur. Furthermore, it demonstrates how to query event data using the Events API and perform complex funnel analysis using HogQL, allowing for deep, custom insights into user behavior.

A comprehensive toolkit designed for advanced data scraping and automation workflows on X/Twitter. Capabilities include deep tweet search, user profile analysis, bulk follower/media export, automated posting (replies, DMs), real-time account monitoring via webhooks, and integration with multiple AI agent platforms (Hermes, OpenClaw). Ideal for market research, social listening, and content automation.

Xquik unlocks Twitter data via REST APIs, MCP tools, and webhooks, covering tweet/user lookups, follower extraction, giveaway draws, trending topics, and accurate account monitoring for real-time automation.

This skill provides a robust solution for monitoring critical forecast changes within Clari. Since Clari lacks native real-time webhooks for all data, this system implements change detection by polling periodic data exports and comparing current snapshots against historical records. It calculates the percentage change and can trigger immediate alerts via platforms like Slack, ensuring users are always aware of significant shifts in revenue forecasts or sales pipelines.

A comprehensive guide and implementation template for building robust data ingestion pipelines into ClickHouse. Supports multiple sources including HTTP webhooks (with batching), Kafka streams, S3, and direct SQL inserts. Demonstrates best practices for data handling, such as deduplication using ReplacingMergeTree and monitoring query logs, ensuring reliable, scalable data analytics.

This skill provides comprehensive access to Bright Data's SERP API and Web Scraper API. It allows users to collect structured search engine results (Google, Bing, Yahoo) synchronously, or trigger large-scale, asynchronous data collections with webhooks. Ideal for market research, SEO analysis, and large-scale data scraping projects.

This guide provides comprehensive technical instructions for optimizing Palantir Foundry costs. Learn to use incremental transforms to drastically reduce compute rebuilds, right-size Spark profiles based on data volume, and migrate from expensive API polling to efficient, event-driven webhooks, ensuring both cost efficiency and system stability.

This comprehensive guide details the process of implementing a secure and robust system for handling Palantir Foundry webhook events. It covers key steps including API-based webhook registration, mandatory signature verification with replay protection, sophisticated event routing for various object lifecycles (create, update, delete), and ensuring idempotent processing using caching mechanisms like Redis. Use this when external microservices must react reliably and immediately to changes within the Foundry Ontology or data assets.