Databases Agent Skills for VS Code

Select only required columns to reduce memory and transfer costs; apply to base queries and relations

Data engineering for batch and streaming pipelines with Airflow, dbt, Spark, and Kafka.

Creates Dataverse tables, columns, and relationships for a Power Pages site based on a data model proposal.

This skill should be used before any Snowflake command to verify MCP connectivity, guide users through access provisioning, and set the…

Salesforce Data Cloud Connect phase. TRIGGER when: user manages Data Cloud connections, connectors, connector metadata, tests a…

AI-powered visual content generation for Salesforce development.

Multi-tenant architecture design. Tenant isolation strategies, RLS, routing, and scale design for SaaS.

Horizontal scaling patterns for multi-tenant databases.

Guides safe, reversible PostgreSQL schema and data migrations using golang-migrate, Prisma, Drizzle, or Django migrations.

Guides PostgreSQL query design, indexing strategy, data types, and row-level security patterns — the query/schema layer, as distinct from…

PostgreSQL database patterns for query optimization, schema design, indexing, and security.

Comprehensive Snowflake development assistant covering SQL best practices, data pipeline design (Dynamic Tables, Streams, Tasks…

Use when the user says 'draw', 'diagram', 'visualize', 'architecture', or needs a visual overview of code structure.

Use when preparing a SIGMOD paper's code and data for the Availability & Reproducibility Initiative (ARI), covering the post-acceptance…

Use when designing or auditing the evaluation of a SIGMOD paper, covering workload realism and standard benchmark usage, baseline tuning…

ACSets (Attributed C-Sets) for categorical database design and DPO rewriting

Record-level CRUD and bulk operations — create, update, delete, upsert, CSV import, multi-table foreign-key loads, AI-generated sample data.

Bulk reads, multi-page iteration, and analytics over Dataverse data.

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

Pre-ship model slim — find and remove UNUSED COLUMNS and orphan measures from a PBIP semantic model before publishing.

Execute comprehensive database smoke tests to validate connectivity, query performance, data integrity, and backup/restore operations…