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Data Engineer

Checked
daffy0208·vlatest·data·MIT

Automates data pipeline creation, cleaning, transformation, and loading for efficient analytics 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 daffy0208/ai-dev-standards --skill data-engineer -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

daffy0208

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.

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  • No pipe-to-shell installers: passed

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

  • Pinned to a commit: passed

    Scanned daffy0208/ai-dev-standards at 32c3241e48.

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

Commit
32c3241e48
Manifest
skills/data-engineer/SKILL.md
Scanned
3 files, 954 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 automates the creation of data pipelines, Extract, Transform, Load (ETL) processes, and overall data infrastructure. It handles data ingestion from various sources, supports both batch and real-time processing, validates data quality, and facilitates analytics workflows like report generation and data export. The skill provides example implementations for common ETL patterns, such as daily synchronization and incremental updates.

When to use it

  • You need to regularly move data from an external API into a database.
  • You want to automate the process of cleaning and transforming raw customer data.
  • You require a system for aggregating data and calculating metrics for reporting purposes.
  • You're building or maintaining a data warehouse and need assistance with schema design and data replication.

Key capabilities

  • ETL Processes: Extract, Transform, Load (ETL) pipelines.
  • Data Ingestion: Ingestion from multiple data sources.
  • Processing Modes: Supports both batch and real-time data processing.
  • Data Quality Validation: Includes mechanisms for validating data quality during the ETL process.
  • Database Schema Design: Assists in designing database schemas.
  • Analytics Support: Facilitates data aggregation, metrics calculation, report generation, and data export.

Example prompts

  • "Create a daily sync pipeline from this external API to my customer database."
  • "Build an incremental ETL process that only updates records changed since the last run."
  • "Design a database schema for storing product information with these fields..."

Tips & gotchas

  • The skill provides example code snippets, but you may need to adapt them to your specific data sources and environments.
  • API keys and secrets are required for authenticating with external services; ensure these are properly configured as environment variables.
  • The provided examples use TypeScript and Vercel Cron for scheduling – familiarity with these technologies might be helpful.