Skip to content
TrustedSkillsbeta
Back to all skills

Data Engineering

Checked
pluginagentmarketplace·vlatest·data

Automates data pipeline creation, optimization, and monitoring within the Plugin Agent Marketplace ecosystem.

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 pluginagentmarketplace/custom-plugin-typescript --skill data-engineering -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

pluginagentmarketplace

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 pluginagentmarketplace/custom-plugin-typescript at 3ed3a92549.

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

Commit
3ed3a92549
Manifest
skills/data/SKILL.md
Scanned
4 files, 90 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 provides data engineering capabilities for AI agents. It allows users to perform tasks related to data processing, transformation, and loading (ETL). The tool can be used to build and manage data pipelines, automate data workflows, and improve the quality of data assets.

When to use it

  • Automating ETL processes: When you need to regularly extract, transform, and load data from various sources into a target system.
  • Building data pipelines: To construct automated sequences of data processing steps for analysis or reporting.
  • Data quality improvement: When needing to cleanse, validate, and standardize datasets.
  • Managing data workflows: To orchestrate complex data-related tasks across different systems and teams.

Key capabilities

  • ETL (Extract, Transform, Load) processes
  • Data pipeline construction
  • Data workflow automation
  • Data quality management

Example prompts

  • "Create a data pipeline to extract customer data from Salesforce, transform it by standardizing address formats, and load it into Snowflake."
  • "Automate the process of cleaning and validating product catalog data daily."
  • "Build an ETL job that aggregates website traffic data from Google Analytics and exports it to a reporting dashboard."

Tips & gotchas

This skill likely requires some understanding of data engineering concepts and familiarity with common data formats. Ensure you have appropriate access credentials for the source and destination systems involved in your data pipelines.