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Etl Sync Job Builder

Checked
patricio0312rev·vlatest·data·MIT

Build automated ETL sync jobs quickly and efficiently, streamlining data workflows for seamless integration and consistent updates.

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 patricio0312rev/skills --skill etl-sync-job-builder -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

patricio0312rev

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 patricio0312rev/skills at 79ea6af485.

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

Commit
79ea6af485
Manifest
db-management/etl-sync-job-builder/SKILL.md
Scanned
1 file, 436 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

ETL Sync Job Builder

What it does

This skill constructs and manages Extract, Transform, Load (ETL) synchronization jobs to keep data consistent across different systems. It automates the workflow of moving, cleaning, and integrating data from source databases into target repositories based on defined rules.

When to use it

  • You need to replicate customer data from a legacy CRM into a modern analytics warehouse nightly.
  • Your team requires automated daily updates of inventory levels between an e-commerce platform and a third-party logistics provider.
  • You must consolidate financial transaction logs from multiple regional servers into a single central ledger for auditing.

Key capabilities

  • Data Extraction: Connects to various source systems to pull raw data efficiently.
  • Transformation Logic: Applies cleaning, formatting, and enrichment rules to the extracted datasets before loading.
  • Synchronization: Ensures target databases reflect the most current state of source data according to specified schedules or triggers.
  • Job Orchestration: Builds complete ETL pipelines as discrete, manageable jobs within the agent's workflow.

Example prompts

  • "Create an ETL job that extracts sales records from our PostgreSQL database every hour and loads them into our Snowflake warehouse."
  • "Build a sync task to transform user profile data from JSON format in our API gateway into SQL tables in our data lake."
  • "Set up an automated pipeline to extract error logs from our application servers, filter for critical errors, and load them into a monitoring dashboard database."

Tips & gotchas

Ensure your AI agent has the necessary read/write permissions for both source and target databases before attempting to build these jobs. Complex transformation rules should be tested in a staging environment first to prevent data corruption during initial synchronization runs.