Skip to content
TrustedSkillsbeta
Back to all skills

Databricks Repl Consolidate

Checked
wedneyyuri·vlatest·data·MIT

This skill consolidates Databricks REPL sessions into a single, runnable notebook for streamlined data exploration and analysis workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add wedneyyuri/databricks-repl --skill databricks-repl-consolidate -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

wedneyyuri

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned wedneyyuri/databricks-repl at ad8663b2b6.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
ad8663b2b6
Manifest
skills/databricks-repl-consolidate/SKILL.md
Scanned
2 files, 138 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill consolidates multiple Databricks REPL (Read-Eval-Print Loop) commands into a single, executable block. It allows users to chain together several REPL operations, such as displaying dataframes or running SQL queries, and execute them sequentially within a Databricks environment. This streamlines workflows by reducing the need for repetitive typing and context switching.

When to use it

  • When you have a series of related commands you want to run in Databricks.
  • For debugging purposes where you need to inspect intermediate results after each step.
  • To automate common data exploration or transformation tasks within a Databricks notebook.
  • When sharing reproducible code snippets that involve multiple REPL interactions.

Key capabilities

  • Consolidates multiple Databricks REPL commands.
  • Executes chained commands sequentially.
  • Supports various REPL operations (e.g., dataframe display, SQL queries).

Example prompts

  • "Run these Databricks commands: display(df1) then select * from table2."
  • "Consolidate this sequence of actions in my Databricks notebook: df = spark.read.csv(...), df.show()."
  • "Execute the following REPL block: print(dbutils.notebook.status). "

Tips & gotchas

This skill requires access to a Databricks environment and familiarity with its REPL commands. Ensure that all referenced tables or dataframes exist within your Databricks workspace for successful execution.