Skill ディレクトリ

AI Agent のための再利用可能な Skill を見つける。

タスクで実際の GitHub Skill を検索し、利用前に Stars、Trust、監査、カテゴリ、インストール経路を確認できます。

すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。

検索結果: databricks

英語版ディレクトリ

A reusable skill kit for AI agents to generate structurally precise and aesthetically standardized draw.io diagrams across major cloud platforms and BPMN, with declarative layout, stencils, and validation.

620
Stars
84/100
信頼
カテゴリ: design-creative監査

Databricks Toolkit for Coding Agents provided by Field Engineering

1.7K
Stars
74/100
信頼
カテゴリ: coding-agents監査

The "Command Line Interactive Controller for Kubernetes"

1.5K
Stars
73/100
信頼
カテゴリ: devops監査

Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform

11K
Stars
74/100
信頼
カテゴリ: support-automation監査

This repo provides a customizable stack for starting new ML projects on Databricks that follow production best-practices out of the box.

686
Stars
72/100
信頼
カテゴリ: ml-automation監査

A SQL transformation engine that type-checks your whole pipeline and catches breaking changes before they run — branches, replay, column-level lineage, compile-time contracts, per-model cost. Adapters: Databricks, Snowflake, BigQuery, DuckDB. Single static Rust binary. Apache 2.0.

267
Stars
69/100
信頼
カテゴリ: data-analysis監査

A set of UDFs and Procedures to extend BigQuery, Snowflake, Redshift, Postgres and Databricks with Spatial Analytics capabilities

210
Stars
65/100
信頼
カテゴリ: geo-science監査
Dbx61

🧱 Databricks CLI eXtensions - aka dbx is a CLI tool for development and advanced Databricks workflows management.

462
Stars
61/100
信頼
カテゴリ: ml-automation監査

End-to-end Data Lakehouse project built on Databricks, following the Medallion Architecture (Bronze, Silver, Gold). Covers real-world data engineering and analytics workflows using Spark, PySpark, SQL, Delta Lake, and Unity Catalog. Designed for learning, portfolio building, and job interviews.

344
Stars
66/100
信頼
カテゴリ: data-analysis監査

This repo is a comprehensive blueprint of how to use dbt to run data pipelines using databricks compute. It showcases modular project structure, data contracts, various tests and incremental models with selectors. No real financial data is used, only dummy data.

74
Stars
60/100
信頼
カテゴリ: finance監査