Skill UI

A comprehensive guide to setting up a minimal working example on Databricks. This skill covers creating a development cluster, uploading and executing notebooks (Python SDK), running tasks as jobs, and setting up a Serverless SQL Warehouse. It is ideal for new users or initializing a basic data engineering project.

A comprehensive guide to implementing best practices for security within Databricks. Learn how to manage secrets using scoped storage, enforce the principle of least privilege via Unity Catalog grants, audit API tokens, and apply advanced data protection techniques like column-level masking and row-level security for enhanced data governance and compliance.

This comprehensive guide provides structured steps and code examples for upgrading Databricks Runtime versions and performing critical data migrations. It covers best practices for version compatibility checking, transitioning from Hive Metastore to Unity Catalog using methods like SYNC and CTAS, and updating deprecated API endpoints, ensuring a smooth platform evolution for data pipelines.

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 skill provides comprehensive guidelines for monitoring Granola usage, tracking team meeting patterns, and building detailed analytics dashboards. It guides users in defining critical metrics (e.g., adoption rate, efficiency score) and establishing robust data pipelines. Users can stream meeting metadata from Granola to data warehouses like BigQuery, enabling deep, customizable reporting and automated weekly insights via services like Zapier and Slack.

This skill provides a comprehensive guide and implementation for deploying a production-ready, containerized integration service using Docker. It connects to the Juicebox API to manage datasets, execute advanced AI-powered analyses, and retrieve structured business insights. The service includes health check mechanisms and supports zero-downtime rolling updates, ensuring reliable real-time data processing and analysis.

This guide provides advanced strategies for optimizing interactions with the Juicebox AI API. It covers crucial best practices such as implementing caching mechanisms (with defined TTLs), executing batch operations for efficiency, managing rate limits, and optimizing data chunking for large datasets. Following these steps can significantly reduce end-to-end analysis time and ensure responsive, scalable data workflows.

This module provides minimal working examples for the OpenEvidence API, designed for clinical intelligence applications. Users can perform complex clinical queries to get treatment recommendations, check potential drug interactions based on patient context, and search for authoritative medical guidelines from major health organizations (e.g., ACC/AHA). Ideal for developing evidence-based healthcare decision support systems.

This comprehensive workflow guides developers through implementing full-stack product analytics using PostHog. It covers key areas including defining event taxonomies, capturing user actions (client-side), identifying and updating user properties, and performing B2B group analytics. It also demonstrates server-side event tracking using posthog-node, ensuring a complete, accurate, and traceable view of user behavior and product usage across web, mobile, and API sources.

This guide provides minimal working examples demonstrating the three core PostHog functionalities: event capture, user identification, and feature flag evaluation. It covers both server-side (Node.js, Python) and client-side (JavaScript) SDK usage, as well as direct API calls, making it perfect for initial integration setup, testing, and learning basic product analytics patterns.

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.

Provide REST API access to ClinPGx, the successor to PharmGKB, for querying gene-drug interactions, CPIC/DPWG/FDA guidelines, allele functions, and evidence that supports precision dosing and pharmacogenomics-driven clinical decisions.