Skill UI

This guide provides a comprehensive framework for minimizing cloud expenditure on Databricks. It covers identifying cost drivers via system billing tables, implementing cluster policies, utilizing spot instances for batch processing, right-sizing SQL warehouses, and automating the shutdown of idle development clusters. Use it when managing cloud spending or optimizing data platform usage.

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.

This skill provides comprehensive observability for the Databricks platform. It enables users to monitor job run histories, track cluster utilization and associated costs (DBU), detect slow SQL queries, and audit access logs. Use it for setting up robust monitoring dashboards, ensuring pipeline health, and optimizing resource consumption across the entire data stack.

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.

Automates guidance for date range analytics, covering SQL, visualization, statistics, and BI, with code generation and validation to support data analytics workflows.

Designs normalized database schemas by analyzing requirements, mapping relationships, generating ERD diagrams, and producing SQL CREATE statements so you can build well-structured relational databases and follow best practices.

Detect SQL injection weaknesses by running the sql-injection-detector plugin against codebases, identifying risky queries, and providing remediation guidance to secure applications.

Provides Django security best practices covering production settings, authentication, authorization, CSRF and SQL injection protection, plus deployment hardening to keep live apps safe.

Comprehensive guide for setting up a complete local development stack for Documenso integrations. It covers project structure, environment variable configuration, running self-hosted services using Docker (PostgreSQL, MailHog), and implementing utility scripts for connection verification and test data cleanup.

Guide for designing, implementing, and scaling event stores in event-sourced systems, covering requirements, technology comparisons, PostgreSQL schemas, and Python persistence patterns.

This skill details best practices for handling and structuring Evernote data. It covers designing local database schemas (SQL), advanced ENML content processing (to Markdown/HTML), managing attachments, and implementing reliable incremental synchronization using Update Sequence Numbers (USN). Ideal for developers building robust applications requiring deep, local data access and integrity checks for Evernote content.

Manages FairDB PostgreSQL backups via pgBackRest and Wasabi S3, automating scheduling, integrity verification, PITR restores, monitoring, and compliance reporting for resilient disaster recovery.