refresh-databricks-skills

Clone upstream Databricks skills and replace outdated ones in .claude/skills.

27|9|Updated Feb 3, 2026
One-click install
npx skills add https://github.com/datasciencemonkey/coding-agents-databricks-apps --skill refresh-databricks-skills
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: refresh-databricks-skills
Source: https://github.com/datasciencemonkey/coding-agents-databricks-apps/tree/main/.claude/skills/refresh-databricks-skills
Command: npx skills add https://github.com/datasciencemonkey/coding-agents-databricks-apps --skill refresh-databricks-skills

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Keeps all Databricks skills up to date by syncing from the upstream ai-dev-kit repository while preserving non-Databricks skills.

Core Features & Use Cases

  • Clones the upstream databricks-skills (depth 1) and replaces all Databricks skill directories in the project.
  • Identifies and preserves non-Databricks skills (superpowers) during refresh.
  • Cleans up after the update and reports counts of added, removed, and updated skills.

Quick Start

Run this command to refresh Databricks skills from the upstream repository and replace the existing Databricks skills while keeping non-Databricks skills intact.

Frequently Asked Questions about refresh-databricks-skills

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I refresh outdated Databricks skills from an upstream repository?

To refresh outdated Databricks skills, this sync process clones the upstream databricks-skills repository at depth 1, removes old Databricks skill directories, and copies fresh versions into .claude/skills.

Can I sync upstream Databricks skills without losing my custom non-Databricks skills?

Yes, syncing upstream Databricks skills preserves non-Databricks skills. The refresh process identifies and retains your custom skill directories while replacing only the outdated Databricks skill versions.

What is the best way to update Databricks skills during project onboarding?

The best way to update Databricks skills during onboarding is running an upstream sync that clones the source repository, replaces old Databricks directories, and reports counts of added, removed, and updated skills.

How does the Databricks skills synchronization process handle cleanup after updating?

Databricks skills synchronization handles cleanup by deleting the cloned upstream repository after copying the fresh Databricks skill directories into .claude/skills, ensuring no residual files remain.

Do I need any dependencies to synchronize Databricks skills from upstream?

No external dependencies are required to synchronize Databricks skills from upstream. The refresh workflow operates independently to clone, replace, and clean up skill directories within your project.

Why does my Databricks skills refresh remove existing skills before copying?

The Databricks skills refresh removes existing skills before copying to prevent conflicts and ensure exact parity with upstream versions, while safely preserving identified non-Databricks skills during the replacement.