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create-scaffold

Generate standardized foundation layers for cookiecutter data engineering projects.

5|1|Updated Sep 23, 2025
Search Tags:#scaffolding#data-engineering#delta-lake#cookiecutter#project-bootstrap#foundation-layer#ddl-migrations
One-click install
npx skills add https://github.com/RDEWAI/Redefining-DataEngineering-With-AI --skill create-scaffold-rdewai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: create-scaffold
Source: https://github.com/RDEWAI/Redefining-DataEngineering-With-AI/tree/main/chapter-6/developer-plugin/skills/create-scaffold
Command: npx skills add https://github.com/RDEWAI/Redefining-DataEngineering-With-AI --skill create-scaffold-rdewai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually setting up the base structure for data engineering projects is time-consuming and error-prone, often leading to missing required directories, configuration files, or infrastructure components that break downstream workflows. This skill eliminates that manual work by generating a complete, standardized foundation layer aligned with project specifications.

Core Features & Use Cases

  • Full Foundation Generation: Creates the entire base project structure including directory trees, Python packaging files (pyproject.toml, Makefile), cross-cutting utility modules, StructType schema contracts, test harnesses, and local development infrastructure.
  • Standards Compliance: Ensures all generated assets follow project-specific coding patterns, naming conventions, and dependency requirements pulled from the project's LLD, DMS, and library handbook at runtime.
  • Use Case: For a new data engineering chapter project, run this skill first to bootstrap all required base assets, so subsequent skills for creating DAGs, ingestion pipelines, and data transformations can build on top without missing foundational components.

Quick Start

Use the create-scaffold skill to generate the complete foundation layer for your new cookiecutter data engineering chapter project, including all required directories, configuration files, utility modules, and local development infrastructure.

Frequently Asked Questions about create-scaffold

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I bootstrap a data engineering project foundation using cookiecutter?▼

To bootstrap a data engineering project foundation, this skill automates creating standardized directory trees, Python packaging files, and utility modules for cookiecutter-based chapter projects. It generates a complete, reproducible base layer aligned with project specifications.

What is included in a standardized data engineering foundation layer?▼

A standardized data engineering foundation layer includes directory trees, pyproject.toml files, Makefiles, cross-cutting utility modules, StructType schema contracts, test harnesses, docker-compose configurations, and Delta Lake DDL migrations.

Why do I need to scaffold a base layer before generating ingestion pipelines and DAGs?▼

You need to scaffold a base layer first because manually setting up project structures is error-prone and leads to missing configuration files. Bootstrapping base assets ensures downstream data engineering generators for pipelines and DAGs build without missing foundational components.

Does this project scaffolding tool generate Delta Lake DDL migrations?▼

Yes, this project scaffolding tool generates Delta Lake DDL migrations. It creates these migrations alongside StructType schema contracts and local development infrastructure, ensuring all assets follow project-specific coding patterns and naming conventions.

Can I use this scaffolding tool to enforce standards from my project's LLD and DMS specifications?▼

Yes, you can use this scaffolding tool to enforce standards from your project's LLD and DMS specifications. It ensures generated assets follow project-specific coding patterns, naming conventions, and dependency requirements pulled from these specifications at runtime.

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