Database migration workflow helper. Use when creating database migrations, modifying SQLAlchemy models, or managing Alembic migrations. Automatically handles model changes, migration creation, and database upgrades.

DBA Admin Agent. 백업, 복구, 보안, 권한 관리를 담당합니다.

DBA Architect Agent. 스키마 설계, 정규화, 데이터 모델링을 담당합니다.

DBA Tuner Agent. 쿼리 최적화, 인덱스 설계, 슬로우 쿼리 분석을 담당합니다.

Execute DDL (Data Definition Language) statements - CREATE, ALTER, DROP tables, indexes, views on 30+ databases using DbCli. CRITICAL - requires mandatory backup before DROP/ALTER operations. Use when user needs to create schema, modify structure, or drop database objects.

Export table data as SQL INSERT statements from 30+ databases using DbCli. Essential for creating backups before dangerous modifications (UPDATE/DELETE/DROP). Use when user needs to backup data, migrate tables, or create portable SQL dumps.

Interactive SQL mode for 30+ databases using DbCli. Provides REPL environment for exploratory queries, rapid prototyping, and database administration. Includes safety prompts before dangerous operations (UPDATE/DELETE/DROP). Use when user wants interactive database session.

List all tables in a database and show table structure (columns, types, constraints) for 30+ databases using DbCli. Use when user wants to explore database schema, see what tables exist, check table structure, or understand column definitions.

Toolkit for analyzing Thai legacy DBF accounting databases using roonpoo, Parquet, and DuckDB.

Transform AI agents into experts on dbt project architecture and medallion layer patterns, providing

This skill enables AI agents to help users monitor dbt execution using the

dbt (data build tool) patterns for model organization, incremental strategies, and testing.

Transform AI agents into experts on dbt command-line operations, model selection patterns, Jinja

Guide AI agents through a systematic, user-choice-driven installation process for dbt-core on local

Complete guide for dbt data transformation including models, tests, documentation, incremental builds, macros, packages, and production workflows

PROACTIVE skill - STOP and invoke BEFORE writing dbt SQL. Validates models against coding conventions for staging, integration, and warehouse layers. Covers naming, SQL structure, field conventions, testing, and documentation. CRITICAL - When about to write .sql files in models/, invoke this skill first, write second. Supports project-specific convention overrides and sqlfluff integration.

dbt best practices for models, tests, documentation, and project organization.

Transform AI agents into experts on dbt materializations, providing guidance on choosing the right

Transform Google BigQuery DDL (views, tables, stored procedures) into production-quality dbt models

Transform IBM DB2 DDL (views, tables, stored procedures) into production-quality dbt models

Transform Hive/Spark/Databricks DDL (views, tables, UDFs) into production-quality dbt models

Transform SQL Server/Azure Synapse T-SQL DDL (views, tables, stored procedures) into

Transform Oracle DDL (views, tables, stored procedures, packages) into production-quality dbt models

Transform PostgreSQL/Greenplum/Netezza DDL (views, tables, stored procedures) into

Transform Amazon Redshift DDL (views, tables, stored procedures) into production-quality dbt models

Transform Snowflake DDL (views, tables, stored procedures) into production-quality dbt models,

Transform Sybase IQ DDL (views, tables, stored procedures) into production-quality dbt models

Transform Teradata DDL (views, tables, stored procedures) into production-quality dbt models

Define and enforce validation rules for dbt models during migration. This skill provides

Transform Vertica DDL (views, tables, stored procedures) into production-quality dbt models

Guide AI agents through the complete migration lifecycle from Snowflake or legacy database systems

Create dbt models following FF Analytics Kimball patterns and 2×2 stat model. This skill should be used when creating staging models, core facts/dimensions, or analytical marts. Guides through model creation with proper grain, tests, External Parquet configuration, and per-model YAML documentation using dbt 1.10+ syntax.

Writes, edits, and creates dbt models following best practices. Use when user needs to create new dbt SQL models, update existing models, or convert raw SQL to dbt format. Handles staging, intermediate, and mart models with proper config blocks, CTEs, and documentation.

Transform AI agents into experts on writing production-quality dbt models, providing guidance on CTE

Comprehensive guide to dbt (data build tool) patterns, modeling best practices, testing strategies, and production workflows for modern data transformation

Transform AI agents into experts on dbt and Snowflake performance optimization, providing guidance

Deploy, manage, and monitor dbt projects natively within Snowflake using web-based workspaces,

Complete step-by-step guide for setting up dbt Projects on Snowflake from beginning to end.

Provides expert-level assistance with dbt Semantic Layer, MetricFlow, semantic models, metrics, dimensions, entities, measures, and BI tool integrations. Use this skill when building semantic models, creating metrics (simple, ratio, cumulative, derived, conversion), debugging validation errors, or integrating with BI tools. Extracted from official dbt documentation and optimized for data practitioners.

ALWAYS USE when working with dbt models, SQL transformations, tests, snapshots, or macros. Use IMMEDIATELY when editing dbt_project.yml, profiles.yml, or creating SQL models. MUST be loaded before any transform-layer work. Enforces dbt owns SQL principle - never parse, validate, or transform SQL in Python.

Transform AI agents into experts on dbt testing strategies, providing guidance on implementing

dbt with TD Trino. Covers profiles.yml setup (method:none, user:TD_API_KEY), required override macros (no CREATE VIEW), TD_INTERVAL in models, and TD Workflow deployment.

Build defensible DCF models with cited sources, Excel export, and sensitivity analysis

Generate presentation layer components using routing-controllers with NestJS-style decorators, class-validator for validation, and automatic Swagger documentation.

Apply Domain-Driven Design, Clean Architecture, CQRS, and command/query patterns to code reviews and feature design. Use when analyzing or designing code in Application, Service, Infrastructure, DataAccess, Validation, Domain, or Functions projects, or when addressing architectural concerns, layering, mapping, entities, value objects, repositories, or validators in the Rome Repair Order Service.

Generate complete Domain-Driven Design bounded contexts with all 4 architectural layers (Domain, Application, Infrastructure, Presentation) for Bun.js + Express + routing-controllers backend applicati

Patterns DDD - Atoll Tourisme. Use when implementing DDD patterns.

Analyzes and refactors code using Domain-Driven Design principles. Use when refactoring domain models, identifying DDD anti-patterns, improving domain clarity, or applying tactical/strategic DDD patterns.

Guide for DDD strategic design - analyzing domains through structured questioning, conducting stakeholder interviews (PM/domain experts/users), and producing Bounded Context analysis, Context Maps, and Ubiquitous Language. Use when user needs help understanding domain boundaries, planning domain interviews, or structuring DDD strategic artifacts.

Créer des tests exhaustifs pour les bounded contexts DDD suivant une approche TDD (Test-Driven Development) avec des standards de coverage stricts.