postgresql-docker
PostgreSQL in containers - Docker, Kubernetes, production configs
PostgreSQL in containers - Docker, Kubernetes, production configs
Optimize PostgreSQL performance - EXPLAIN ANALYZE, indexing, query tuning
Generate production-ready Row Level Security (RLS) policies for Supabase tables with is_super_admin() bypass, proper USING/WITH CHECK, and common relationship patterns; use when creating RLS policies, securing tables, implementing data access controls, or securing storage buckets
数据库管理统一接口,支持 Supabase (PostgreSQL)、PlanetScale (MySQL)、Turso (SQLite) 等主流数据库服务。 提供连接管理、CRUD 操作、迁移、RLS 策略配置等功能。用于快速集成数据库到 Agent 系统。
ALWAYS USE when building semantic layer, working with metrics/dimensions, or integrating dbt with Cube consumption APIs. Use IMMEDIATELY when working with Cube REST API, GraphQL queries, or Postgres wire protocol (psycopg2 connections). Provides research steps for data modeling, dbt integration, MEASURE() syntax, and API validation.
Generate comprehensive PySpark-based data quality validation tests for Databricks tables. Use when creating automated tests for data completeness, accuracy, consistency, and conformity, or when user mentions test generation, data validation, quality monitoring, or PySpark test frameworks.
Connect to and inspect data sources. Use this skill when you need to verify data access, inspect table schemas, check row counts, or understand the structure of a dataset before performing analysis.
Generate DuckDB SQL queries. Use when user asks about DuckDB queries, data analysis, exploring .ddb database files, CSV files, Parquet files, wants help editing/improving SQL, asks to use the duckdb skill, references duckdb assets, or wants to initialize/setup duckdb analysis.
Convert natural language queries to SQL for PostgreSQL databases. Use this skill when users want to query pg_mcp_test_small (blog), pg_mcp_test_medium (ecommerce), or pg_mcp_test_large (ERP) databases using natural language descriptions. Generates safe, read-only SQL queries with validation and execution.
SQL Query Designer skill that generates optimized SQL queries from natural language requests and table schemas. Trigger terms: SQL, query, database, SELECT, JOIN, INSERT, UPDATE, DELETE, WHERE, GROUP BY, ORDER BY, LIMIT, schema, table, index, クエリ, データベース, テーブル, 検索, 抽出, 取得, 集計, 分析, 統計, レポート, 売上, ユーザー, 商品, 注文, データ, 情報 Use when: User needs help designing SQL queries, optimizing database queries, or translating natural language requests into SQL.
Query databases and explore data. Use when the user mentions database, query, SQL, table, schema, data exploration, "check the data", "look at the database", "what's in the table", "show me records", "find in database", PostgreSQL, MySQL, SQLite, cross-database joins, data validation, or export query results. Also triggers on: exploring schemas, sampling data, running analytics queries, checking data quality, or any task involving database operations.
Use this skill when writing Supabase queries, SQL statements, or database-related TypeScript code. Ensures optimal query patterns, performance, and best practices.
Design database schemas, create tables, manage migrations, and optimize database structures. Use for relational and non-relational database implementations.
Analyze ClickHouse table structure, partitioning, ORDER BY keys, materialized views, and identify schema design anti-patterns. Use for table design issues and optimization.
Analyze database schema and migrations for onboarding. Use when exploring schema folders, understanding table structures, analyzing migration files (golang-migrate, goose, sql-migrate, atlas), reviewing foreign key relationships, identifying indexes, understanding data models, and generating database documentation. Supports SQL migration files and Go-based migration tools.
Drizzle ORM patterns with PostgreSQL and PostGIS for spatial data. Covers schema definition, queries, migrations, spatial operations, and upsert patterns. Use when working with database operations, schema changes, or spatial queries.
Database migration management with Alembic for SQLAlchemy. Use when creating or modifying database schemas, tables, or indexes.
Design, review, and evolve the TRR Backend 2025 database (Supabase/Postgres + RLS) including schema modeling, indexes, migrations, rollout plans, and S3 metadata patterns. Use when adding or changing tables, RLS policies, indexes, or storage metadata; when reviewing query performance or migration safety; or when preparing DB design reviews and checklists for TRR.
SQL best practices with pgTAP, sqlfluff 3.2, query optimization, and migration management.
Explore PostgreSQL and DuckDB schemas, tables, and sample data. Use when investigating data issues, checking table structures, or when user asks "DB 구조 알려줘", "데이터 확인해줘".