技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: databricks

英文目录

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
信任
分类: design-creative审计

Databricks Toolkit for Coding Agents provided by Field Engineering

1.7K
Stars
74/100
信任
分类: coding-agents审计

The "Command Line Interactive Controller for Kubernetes"

1.5K
Stars
73/100
信任
分类: devops审计

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

11K
Stars
74/100
信任
分类: support-automation审计

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
信任
分类: ml-automation审计

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
信任
分类: data-analysis审计

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

210
Stars
65/100
信任
分类: geo-science审计
Dbx61

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

462
Stars
61/100
信任
分类: ml-automation审计

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
信任
分类: data-analysis审计

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
信任
分类: finance审计