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domain-scoping

Guide data domain definition through interviews and modeling strategy decisions.

1|Updated Feb 7, 2026
Search Tags:#scoping#data modeling#data architecture#data governance#domain driven design#canonical model
One-click install
npx skills add https://github.com/Semprini/md-ddl --skill domain-scoping
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: domain-scoping
Source: https://github.com/Semprini/md-ddl/tree/main/agents/agent-ontology/skills/domain-scoping
Command: npx skills add https://github.com/Semprini/md-ddl --skill domain-scoping

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill guides users through the process of defining new data domains, ensuring all necessary aspects are considered before modeling begins, and helps decide between canonical and domain-driven modeling strategies.

Core Features & Use Cases

  • Domain Definition Protocol: Follows a structured interview to understand business purpose, concepts, boundaries, and governance.
  • Modeling Strategy Guidance: Helps choose between Canonical and Domain-Driven approaches based on organizational needs.
  • Requirements Intake: Processes structured documents like spreadsheets or user stories to map them to modeling decisions.
  • Use Case: When starting a new project to model customer data, this skill will interview stakeholders to understand what "customer" means in different contexts, who uses it, and what governance rules apply, before drafting the domain model.

Quick Start

Begin the domain scoping process by asking the user to describe the business purpose of the new domain.

Frequently Asked Questions about domain-scoping

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

FAQPage Schema
How do I define and scope a new data domain before modeling begins?▼

To define a new data domain, you must evaluate business purpose, concepts, boundaries, and governance. This domain scoping process uses structured interviews and requirements intake from artifacts to ensure all aspects are considered before modeling starts.

When should I choose a canonical model over domain driven design for data architecture?▼

Choosing a canonical model over domain driven design depends on organizational needs. Canonical modeling translates baselines to a unified format, while domain driven design structures architecture around specific business contexts.

How do I map structured data requirements from spreadsheets to modeling decisions?▼

To map data requirements from spreadsheets, process the structured artifacts through a requirements intake protocol. This translates baselines and user stories into concrete modeling strategy decisions for the new domain.

What is the best way to scope a brownfield data domain with existing baselines?▼

Scoping a brownfield data domain involves translating existing baselines to canonical models. The process evaluates current artifacts and structures to integrate or refactor the domain without starting from scratch.

What questions should I ask stakeholders to understand domain boundaries and governance?▼

Stakeholder interviews for domain boundaries should cover business purpose, core concepts, and data governance rules. This structured protocol clarifies what entities mean in different contexts before drafting the domain model.

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