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Guides data engineering patterns for ETL pipelines, Spark analytics, and quality checks, showcasing Python and SQL snippets to extract, transform, load, validate, and model sales data in modern warehouses.

A protocol that provides LLM agents with persistent structural memory of a codebase. It maps the project as a directed graph, tracking not only dependencies (what imports what) but also the 'reasons' (why it connects). This allows agents to understand context, perform impact analysis, and navigate large repositories without loading the entire source code into the context window.

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.

This skill provides expert guidance for modern, multi-cloud database administration. It covers comprehensive knowledge across AWS, Azure, and GCP platforms, spanning relational, NoSQL, and graph databases. Key areas include Infrastructure as Code (Terraform, Flyway), achieving high availability, disaster recovery, advanced performance optimization, and ensuring strict regulatory compliance (HIPAA, GDPR). It is essential for managing complex, highly reliable cloud data architectures.

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.

Specializes in generating production-grade SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, and SQL Server. Provides comprehensive plans covering data integrity, detailed rollback procedures, performance optimization, and validation checks for critical schema changes.