create-lld

Generate a 14-section Low-Level Design document from approved data engineering artifacts.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Technical leads waste hours manually translating upstream data engineering artifacts into detailed implementation specifications. This Skill automates the creation of comprehensive Low-Level Design documents, ensuring consistency, completeness, and alignment with project scaffolds.

Core Features & Use Cases

  • Automated LLD Generation: Produces a 14-section Low-Level Design document from DRD, HLD, DMS, STM, and DQS artifacts.
  • Implementation Elicitation: Uses structured Q&A to gather missing implementation decisions on DAG design, performance, and deployment before generating output.
  • Artifact Validation: Enforces an upstream approval gate, stopping work if any required artifact is missing or unapproved.
  • Use Case: A technical lead can generate a complete LLD, DAG definition, and implementation sequence for a new medallion pipeline in minutes rather than days.

Quick Start

Use the create-lld skill to generate a complete low-level design document for your data pipeline from approved upstream artifacts.

Frequently Asked Questions about create-lld

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

FAQPage Schema
How do I generate a low-level design document from upstream data engineering artifacts?

To generate a low-level design document, you can use an automated tool to translate approved DRD, HLD, DMS, STM, and DQS artifacts into build-ready implementation specifications. This replaces manual translation, ensuring alignment with your project scaffold.

What upstream artifacts are required for low-level design generation?

Low-level design generation requires approved DRD, HLD, DMS, STM, and DQS artifacts. An enforced validation gate stops the process if any required upstream data engineering artifact is missing or unapproved.

Does low-level design generation work with data pipeline DAG design?

Yes, low-level design generation supports data pipeline DAG design by using structured elicitation to gather missing implementation decisions on DAG design, performance, and deployment before outputting the final specifications.

Can I use cookiecutter project scaffolds for low-level design generation?

Yes, you can use a cookiecutter project scaffold for low-level design generation. The process requires a cookiecutter scaffold and technical inputs for development standards, infrastructure specs, and orchestration patterns to ensure build-ready output.

What is the best way to translate business requirements into implementation specifications for a data pipeline?

The best way to translate business requirements into implementation specifications is to automate the creation of a comprehensive low-level design document. This ensures consistency and completeness across all 14 sections of your data pipeline plan.

Why does low-level design generation stop if my data mapping specification is unapproved?

Low-level design generation stops if your data mapping specification is unapproved because an artifact validation gate enforces upstream approvals. This prevents translating incomplete or unapproved business requirements into flawed implementation plans.