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Dbt Data Transformation

Checked
manutej·vlatest·data

Automates dbt project execution, testing, and documentation to streamline data transformations and ensure quality.

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 manutej/luxor-claude-marketplace --skill dbt-data-transformation -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

manutej

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 manutej/luxor-claude-marketplace at 1861cc9720.

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

Commit
1861cc9720
Manifest
plugins/luxor-data-engineering/skills/dbt-data-transformation/SKILL.md
Scanned
3 files, 4,679 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 enables AI agents to automate and manage dbt (data build tool) projects for analytics engineering. It covers a wide range of tasks including model development, testing, documentation generation, incremental builds, macro creation, package management, and deployment workflows. Essentially, the agent can assist in building and maintaining data transformation pipelines using dbt's software engineering best practices.

When to use it

  • Building data transformation pipelines for analytics and business intelligence.
  • Creating a data warehouse with modular, testable SQL transformations.
  • Implementing ELT (Extract, Load, Transform) workflows.
  • Developing dimensional models (facts, dimensions).
  • Managing complex SQL dependencies and data lineage.

Key capabilities

  • Model Development: Writing SQL SELECT statements as dbt models using CTEs and referencing sources with {{ source() }}.
  • Testing: Defining and executing data quality tests within the dbt framework.
  • Documentation: Generating searchable data dictionaries automatically.
  • Macro Creation: Developing reusable Jinja-SQL functions (macros).
  • Package Management: Handling dependencies and managing dbt packages.
  • Deployment: Supporting CI/CD pipelines for deploying data transformations.
  • Incremental Builds: Creating incremental models for large datasets.

Example prompts

  • "Create a dbt model to transform the 'orders' table from the 'jaffle_shop' source."
  • "Define a data quality test for the 'stg_orders' model."
  • "Generate documentation for all dbt models in my project."

Tips & gotchas

  • This skill requires familiarity with dbt concepts and terminology.
  • Models are defined using only SELECT statements; no Data Definition Language (DDL) is supported within the models themselves.
  • The agent will leverage Jinja templating for SQL transformation logic.