Skill UI

This skill provides comprehensive guidance on using LibreOffice Base for full-cycle database management. Users can create ODB databases, define schemas, manage tables, and establish relationships. It supports connecting to various external databases (MySQL, PostgreSQL, etc.), performing complex data operations, and automating professional reports and forms using SQL and Python scripting (UNO). Ideal for building data-driven applications.

This guide provides comprehensive patterns and best practices for working with ClickHouse, a high-performance OLAP database. It covers advanced topics such as MergeTree engine design, efficient query optimization (filtering, aggregations, window functions), bulk/streaming data ingestion, materialized view creation, and performance monitoring techniques, ensuring optimal performance for large-scale analytical workloads.

A comprehensive guide for migrating user authentication systems from major providers like Auth0, Firebase, Supabase, or NextAuth to Clerk. It covers essential steps including user data export, bulk import, updating database references, and replacing client and server-side authentication code for a smooth, phased transition.

Learn how to configure and implement robust backend endpoints to handle webhooks from Clerk. This guide covers processing user lifecycle events (creation, update, deletion) and organization events, ensuring seamless data synchronization to your external database. It emphasizes secure practices like Svix signature verification and idempotency protection.

Guides ClickHouse database architects through schema designs, query optimization, ingestion strategies, and monitoring techniques tailored for high-performance analytical workloads.

Automates CodeQL database builds, suite selection, and taint-aware scans to surface security and quality issues across supported languages, handling output directories, SARIF results, and extensions in one workflow.

This comprehensive template provides a production-grade reference architecture for CodeRabbit AI code reviews. It is designed to guide teams in establishing rigorous coding standards by defining specific, best-practice instructions for various layers (API, Database, Authentication, Frontend, CI/CD, Infrastructure). Use this as a robust starting point to build a comprehensive, automated, and secure code quality review process.

This skill provides a comprehensive guide to configuring CodeRabbit for advanced, security-focused code reviews. It teaches how to implement rules for detecting hardcoded secrets, common vulnerabilities (like SQL injection and XSS), and enforcing secure coding standards across APIs, databases, and infrastructure code. Use this when hardening a codebase's security posture or ensuring compliance with industry standards.

Automates configuring and aggregating infrastructure metrics across compute, storage, network, containers, load balancers, and databases with Prometheus, Datadog, or CloudWatch for dashboards and capacity tracking.

Compares PostgreSQL or MySQL schemas using the database-diff-tool, produces transaction-safe migration scripts and rollback procedures, and outlines synchronization steps for staging/production deployments.

Guidelines for building Convex backends with TypeScript, detailing syntax, validators, schema design, queries, mutations, actions, scheduling, and file storage so you can implement Convex database operations, real-time updates, and cron jobs consistently.

Provides automated guidance for designing and implementing cron job schedulers in backend projects, covering best practices, production-ready code, and validation for node.js, Python, Go, databases, and microservices patterns.