Discover tools data engineering skills, compare source repositories and read the instructions for each workflow.
This skill should be used when seeding databases with realistic fake data for development, testing, or staging environments. Supports PostgreSQL, MySQL, SQLite, MongoDB with ORM-based seeding (SQLAlchemy, Djang...
Data Lake architecture and management including medallion architecture (bronze/silver/gold zones), data catalog with AWS Glue, partitioning strategies, schema evolution, data quality, governance, cost optimizat...
Proactive skill for validating dbt models against coding conventions. Auto-activates when creating, reviewing, or refactoring dbt models in staging, integration, or warehouse layers. Validates naming, SQL struc...
Specialized skill for designing AWS DynamoDB single-table schemas with optimized access patterns. Use when modeling data, designing table structure, or optimizing DynamoDB queries for production applications.
Manage PostgreSQL databases using Postgres MCP. Query data, inspect schemas, analyze table structures, run migrations, debug database issues, and manage test data. Use when working with databases, debugging que...
Comprehensive Python data engineering patterns for AWS Data Lake, including PySpark, Pandas, Apache Airflow, AWS Glue, ETL pipelines, data quality, schema management, performance optimization, FastAPI services,...
Automatically applies when optimizing database queries. Ensures EXPLAIN analysis, proper indexing, N+1 prevention, query performance monitoring, and efficient SQL patterns.
Databricks Apps deployment, debugging, and configuration management. Use when working with Databricks Apps issues including deployment failures, app configuration (app.yaml), granting permissions to SQL warehou...
Use the Databuddy REST API for programmatic access to analytics data. Use when querying analytics data, building custom dashboards, sending events via API, or integrating analytics into backend services.
Create Databricks AI/BI dashboard JSON files in lvdash.json format. Triggers: ダッシュボード, 可視化, visualize, create dashboard, build dashboard, dashboard JSON, lvdash.json, BI dashboard, visualization, char...
Integrate Databuddy analytics into applications using the SDK or REST API. Use when implementing analytics tracking, feature flags, custom events, Web Vitals, error tracking, LLM observability, or querying anal...
Generate Konveyor analyzer migration rules from migration guides using AI
Databricks billing data analysis and cost calculation using system.billing tables. Triggers: cost analysis, billing report, DBU usage, SKU costs, monthly expenses, job costs, warehouse costs, spending breakdown...
Databricks System Tables の分析・クエリ作成支援。Unity Catalog の system カタログに格納された運用データ（課金、監査ログ、ジョブ実行、クエリ履歴、リネージュ、コンピュートなど）を活用した分析・調査を行う際に使用...
Unity Catalog metadata inspection, data exploration, and permission management. Triggers: list catalogs, show tables, describe table, check permissions, grant access, table not found, access denied, explore sch...
Databricks Jobs management, monitoring, and debugging. Use for job status checks, run history, failure investigation, job execution, and historical analysis. Triggers: job status, run history, job failure, debu...
A skill for using Databricks SQL (SQL Warehouse) via SDK. Supports both Python (databricks-sql-connector) and Node.js (@databricks/sql). Use when: - Connecting to SQL Warehouse from Databricks Apps to execute...
This skill should be used when the user asks to "generate a pipeline", "create ETL", "build ELT", "ingest data", or "load data into warehouse".
Automatically create GitHub issues when DataQL errors occur, with duplicate validation. Use when DataQL commands fail or produce unexpected errors.
This skill should be used when the user asks to "write SQL", "optimize a query", "explain this SQL", or needs help with database queries and SQL best practices.
WHAT: Transform API responses into domain models with transformers, helpers, and utilities. WHEN: converting API data shapes, implementing data pipelines, organizing transformation logic. KEYWORDS: transformer,...
Complete knowledge of the PostgreSQL schema, Prisma ORM patterns, indexes, and migration workflows.
When writing complex features or significant refactors or user ask explicitly, use an ExecPlan from design to implementation.
Analyze McDougall-style fuel business data (SQLite via Laravel) to answer business questions, build KPIs, propose dashboards, and deliver actionable insights for operations leadership.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.