348 skills · sorted by relevance
Design and review PostgreSQL database schemas by choosing suitable column types, keys, constraints, and indexes. It also guides decisions about large-table partitioning, flexible JSONB data, and schema changes on a live database without downtime.
Review PostgreSQL queries and data designs using execution plans, which show how queries run, and targeted index recommendations. Get guidance on JSONB, arrays, full-text search, analytical queries, extensions, and routine database maintenance.
Create and connect to managed MySQL, PostgreSQL, or SQL Server databases on Google Cloud. This skill guides instance setup, database creation, access permissions, and connection steps, with references for backups, security, and Terraform configuration.
Migrate the database access layer of a .NET/C# application from Oracle to PostgreSQL with Npgsql. Update packages, connection settings, parameter types, SQL, and stored procedure calls, then build the copied project and track completed migration tasks.
Create and manage MySQL, PostgreSQL, and SQL Server databases on Google Cloud. Covers instance setup, users, backups, availability, and secure connections, with a PostgreSQL walkthrough and references for application connectors and Terraform configuration.
Get documentation-based help with PostgreSQL queries, database design, administration, and performance tuning. The supplied reference also explains connection settings and libpq, PostgreSQL’s C client library, for investigating connection failures and implementing connection handling.
Azure PostgreSQL Flexible Server SDK for .NET. Database management for PostgreSQL Flexible Server deployments. Use for creating servers, databases, firewall rules, configurations, backups, and high availability. Triggers: "PostgreSQL", "PostgreSqlFlexibleServer", "PostgreSQL Flexible Server", "Azure Database for PostgreSQL", "PostgreSQL database management", "PostgreSQL firewall", "PostgreSQL backup", "Postgres".
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Review PostgreSQL code for database design, performance, and security issues. Get improvement suggestions covering JSONB, a binary JSON format, arrays, indexes, custom data types, functions, extensions, and rules that control access to individual rows.
Convert Oracle stored procedures and functions, programs stored inside a database, into PostgreSQL equivalents. Preserve parameters and control flow while adapting Oracle syntax, resolving types, and mapping text sorting rules to the target environment.
Improve PostgreSQL performance through a staged workflow covering slow query analysis, indexes that speed up data access, query rewrites, configuration tuning, routine maintenance, and monitoring for production databases.
Provision a PostgreSQL database with Neon Instagres and save connection settings for application use and migrations. Includes setup examples for Drizzle and Prisma, initial data loading, and claiming a temporary database to keep using it.
Guide PostgreSQL database design and troubleshooting with examples for faster queries, indexes that speed up searches, suitable data types, and row-level access rules. Also covers connection settings and SQL for investigating performance problems.
Design and build backend services with API scaffolding, database migrations, authentication reviews, and load testing. Generate route handlers from OpenAPI specifications, identify PostgreSQL optimization opportunities, and compare architecture choices against traffic, data sensitivity, and reliability requirements.
Investigate slow PostgreSQL queries in Paperclip, reproduce their cost locally, and implement measured fixes. Compare performance and returned results, add regression coverage, and carry pull requests through review and automated checks.
Turn defects found during Oracle-to-PostgreSQL migration into structured bug reports. Document expected and actual behavior, reproduction steps, severity, root causes, proposed changes, and validation on both databases so teams can act on the findings.
Create integration tests for .NET database access before migrating from Oracle to PostgreSQL. The tests record expected Oracle behavior with controlled test data and portable checks, providing a baseline for later migration validation.
Review every project in a .NET solution for Oracle dependencies, classify its migration status, and create a saved PostgreSQL migration plan with a project inventory and an order that prioritizes shared libraries.
Create and administer AlloyDB for PostgreSQL databases, including clusters, instances, backups, secure connections, and access permissions. It also covers command-line operations, infrastructure configuration, and MCP tools that let agents automate database tasks.
PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem. Use when writing or tuning PostgreSQL-specific SQL or choosing PostgreSQL features for a design.
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Analyzes one .NET project to plan integration tests for an Oracle-to-PostgreSQL migration. Identifies database access methods, prioritizes migration risks, and documents test cases, seed data, and coverage, including empty strings, NULL values, and timezone behavior.
Set up and manage AlloyDB for PostgreSQL clusters, instances, and backups. Includes guidance for MCP integration, a way for agents to operate databases, plus references for application connections, Terraform, authentication, and AI search capabilities.
Design PostgreSQL tables by choosing data types, validation rules, and indexes that match actual queries. The skill also guides JSONB usage, partitioning large tables, and planning schema changes with attention to read and write workloads.
Design PostgreSQL tables around actual queries and data volumes. Choose data types, validation rules, and indexes, then plan large table partitioning, access rules for individual rows, and schema changes with migration and rollback considerations.
Write and improve SQL for major data warehouses, accounting for differences in their syntax. Use it to build analytical queries, translate existing SQL, investigate errors, and review slow queries for performance improvements.