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.

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

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.

This comprehensive workflow guides the entire database lifecycle, from initial architecture design (covering both SQL and NoSQL) to advanced implementation, optimization, and maintenance. It covers crucial stages like schema design, implementing migrations, optimizing query performance, developing robust data pipelines (using tools like Airflow and dbt), and managing data quality and operations. Ideal for engineers building complex, production-grade data systems.

An expert architect specializing in designing, optimizing, and scaling entire data layers from inception (greenfield) to re-architecture. Proficient in selecting the optimal database technology (SQL, NoSQL, Graph, Time-series), designing robust schemas, implementing sophisticated indexing strategies, and planning complex migration paths. Suitable for defining data storage solutions that meet high performance, scalability, and data integrity requirements.

Provides a practical checklist and principles for designing database schemas, indexing strategies, query optimization, and migration planning for both SQL and NoSQL systems, plus guidance on spotting and fixing N+1 issues and denormalization trade-offs.

A comprehensive, expert-level skill for designing, analyzing, and optimizing robust database schemas. It covers normalization, index tuning, choosing between SQL/NoSQL, and implementing zero-downtime data migrations. Provides systematic workflows for schema analysis, performance modeling, and advanced SQL pattern generation.

This skill automates the creation of comprehensive documentation for relational databases (PostgreSQL/MySQL). By introspecting live schemas, it extracts detailed metadata including table structures, column descriptions, primary/foreign key relationships, indexes, views, and stored procedures. The output provides a data dictionary, entity-relationship map, and schema statistics, crucial for knowledge transfer and database lifecycle management.

Master the advanced process of database schema and data migrations across major ORMs (Sequelize, TypeORM, Prisma). This skill provides best practices for handling complex transformations, including implementing zero-downtime deployments, renaming columns, changing data types, and executing complex data restructuring. It emphasizes robust rollback strategies to ensure data integrity during critical database updates.

A comprehensive guide covering best practices for database migrations. It addresses schema changes, data migrations, and rollbacks for major databases (PostgreSQL, MySQL) and modern ORMs (Prisma, Drizzle, etc.). Learn how to implement safe, reversible, and zero-downtime schema updates for production environments.

This guide provides expert patterns for building robust, observable infrastructure for database migrations. It covers real-time monitoring using Change Data Capture (CDC), metrics collection (Prometheus/Grafana), and anomaly detection. Use this skill when setting up CDC pipelines (e.g., Debezium with Kafka) or implementing comprehensive observability for database schema changes and data synchronization processes.