update-scaffold

Update project scaffold files in place while preserving custom code.

5|1|Updated Sep 23, 2025
One-click install
npx skills add https://github.com/RDEWAI/Redefining-DataEngineering-With-AI --skill update-scaffold
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: update-scaffold
Source: https://github.com/RDEWAI/Redefining-DataEngineering-With-AI/tree/main/chapter-6/developer-plugin/skills/update-scaffold
Command: npx skills add https://github.com/RDEWAI/Redefining-DataEngineering-With-AI --skill update-scaffold

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually updating project scaffold files after logical layer design revisions, data model changes, or upstream template updates is error-prone and risks overwriting custom user edits, missing version synchronization, or accidentally deleting critical project files.

Core Features & Use Cases

  • In-place scaffold updates: Adds missing directories, modules, and configuration files to existing projects without deleting any existing content, serving as the safe counterpart to the create-scaffold skill.
  • Multi-mode synchronization: Supports syncing StructType schema contracts with revised data models or source DuckDB schemas, reconciling infrastructure files (docker-compose, pyproject.toml, Makefile, Dockerfiles) against pinned library versions, and aligning projects with updated upstream cookiecutter templates.
  • Use Case: If your team revises the project's logical layer design to add a new data processing layer, use this skill to automatically add the required module structure and update configuration files while preserving all your custom code changes.

Quick Start

Use the update-scaffold skill to sync your project's infrastructure configuration files with the latest pinned library versions after a Spark or Delta version bump.

Frequently Asked Questions about update-scaffold

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

FAQPage Schema
How do I update project scaffolds without overwriting custom code modifications?

To update project scaffolds safely, apply in-place file patching that adds missing directories and synchronizes infrastructure configuration while explicitly preserving user-edited files and custom code modifications from being overwritten or deleted.

How do I synchronize StructType schema contracts with revised data models?

Synchronize StructType schema contracts by reconciling existing schema definitions against the revised data model specifications or source DuckDB schemas, ensuring downstream infrastructure stays aligned with the canonical source of truth.

What is the best way to sync pyproject.toml dependency pins after a Spark or Delta version bump?

Syncing pyproject.toml dependency pins after version bumps requires reconciling infrastructure files against pinned library version caches, ensuring Dockerfiles, Makefiles, and docker-compose configurations stay aligned with the updated canonical versions.

Can I align an existing project structure with an updated upstream cookiecutter template?

Yes, you can align existing projects with updated upstream cookiecutter templates by applying multi-mode synchronization that patches the project directory structure and configuration files without deleting existing content or custom edits.

Does updating infrastructure configuration files risk deleting critical project files?

Updating infrastructure configuration files poses no deletion risk when using in-place scaffold updates, which add missing modules and configurations while explicitly protecting critical project files and custom code modifications from being overwritten.

When do I need to reconcile infrastructure configuration and schema contracts in a data engineering project?

You need to reconcile infrastructure configuration and schema contracts when logical layer designs change, data models are revised, or upstream project templates update, requiring synchronization of Dockerfiles, dependency pins, and StructType definitions.