dbt project structure using medallion architecture (bronze/silver/gold layers). Use this skill when planning project organization, establishing folder structure, defining naming conventions, implementing layer-based configuration, or ensuring proper model dependencies and architectural patterns.

Monitor dbt execution using the dbt Artifacts package. Use this skill when you need to track test and model execution history, analyze run patterns over time, monitor data quality metrics, or enable programmatic access to dbt execution metadata across any dbt version or platform.

dbt command-line operations, model selection syntax, Jinja patterns, troubleshooting, and debugging. Use this skill when running dbt commands, selecting specific models, debugging compilation errors, using Jinja macros, or troubleshooting dbt execution issues.

Choosing and implementing dbt materializations (ephemeral, view, table, incremental, snapshots, Python models). Use this skill when deciding on materialization strategy, implementing incremental models, setting up snapshots for SCD Type 2 tracking, or creating Python models for machine learning workloads.

Complete workflow for migrating database tables, views, and stored procedures to dbt projects on Snowflake. Orchestrates discovery, planning, placeholder creation, view/procedure conversion, testing, and deployment. Delegates platform-specific syntax translation to source-specific skills.

Convert Google BigQuery DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from BigQuery to dbt code, generating schema.yml files with tests and documentation, or migrating BigQuery SQL to follow dbt best practices.

Convert Hive/Spark/Databricks DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or UDFs from Hive, Spark, or Databricks to dbt code, generating schema.yml files with tests and documentation, or migrating HiveQL to follow dbt best practices.

Convert Oracle DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from Oracle to dbt code, generating schema.yml files with tests and documentation, or migrating Oracle PL/SQL to follow dbt best practices.

Convert PostgreSQL/Greenplum/Netezza DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from PostgreSQL, Greenplum, or Netezza to dbt code, generating schema.yml files with tests and documentation, or migrating PostgreSQL SQL to follow dbt best practices.

Convert Amazon Redshift DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from Redshift to dbt code, generating schema.yml files with tests and documentation, or migrating Redshift SQL to follow dbt best practices.

Convert Sybase IQ DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from Sybase IQ to dbt code, generating schema.yml files with tests and documentation, or migrating Sybase SQL to follow dbt best practices.

Convert Teradata DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from Teradata to dbt code, generating schema.yml files with tests and documentation, or migrating Teradata SQL to follow dbt best practices.

Comprehensive validation skill for dbt models and schema YAML files. Defines validation rules, common anti-patterns to detect, and auto-fix suggestions. Integrates with Claude Code hooks to enforce quality standards during migration.

Convert Vertica DDL to dbt models compatible with Snowflake. This skill should be used when converting views, tables, or stored procedures from Vertica to dbt code, generating schema.yml files with tests and documentation, or migrating Vertica SQL to follow dbt best practices.

Writing dbt models with proper CTE patterns, SQL structure, and layer-specific templates. Use this skill when writing or refactoring dbt models, implementing CTE patterns, creating staging/intermediate/mart models, or ensuring proper SQL structure and dependencies.

Optimizing dbt and Snowflake performance through materialization choices, clustering keys, warehouse sizing, and query optimization. Use this skill when addressing slow model builds, optimizing query performance, sizing warehouses, implementing clustering strategies, or troubleshooting performance issues.

Deploying, managing, executing, and monitoring dbt projects natively within Snowflake using dbt PROJECT objects and event tables. Use this skill when you want to set up dbt development workspaces, deploy projects to Snowflake, schedule automated runs, monitor execution with event tables, or enable team collaboration directly in Snowflake.

dbt testing strategies using dbt_constraints for database-level enforcement, generic tests, and singular tests. Use this skill when implementing data quality checks, adding primary/foreign key constraints, creating custom tests, or establishing comprehensive testing frameworks across bronze/silver/gold layers.

Deploying and managing Snowflake database objects using version control with schemachange. Use this skill when you need to manage database migrations for objects not handled by dbt, implement CI/CD pipelines for schema changes, or coordinate deployments across multiple environments.

Manage and synchronize AI agent skills from local SKILL.md files and remote Git repositories, generating Cursor rules with Agent Skills specification XML. This skill should be used when users need to sync skills, add/remove skill repositories, or set up the skills infrastructure.