Skip to content
Back to skills

Minimal

ASecurity

Essential questions to ask before designing a data model

  • 2 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added September 10, 2026
design

Security analysis

A100/100

Scanned September 10, 2026

npx -y skills add snoodleboot-io/prompticorn --skill minimal --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Minimal?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Minimal
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/snoodleboot-io-minimal-2e46cb16/badge)](https://www.skillsdirectory.com/skills/snoodleboot-io-minimal-2e46cb16)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: data-model-discovery
description: Essential questions to ask before designing a data model
languages: [all]
subagents: [architect/data-model]
tools_needed: []
---

## Data Model Discovery Questions

Before designing any data model, ask these questions:

1. **What are the core entities and their relationships?**
   - Identify nouns in requirements
   - Map relationships (1:1, 1:many, many:many)

2. **What are the most common read patterns?**
   - Which queries will run most frequently?
   - What filters/sorts are needed?

3. **What are the most common write patterns?**
   - Insert frequency and volume
   - Update patterns and triggers

4. **Are there soft-delete, audit trail, or versioning requirements?**
   - Do records need to be recoverable?
   - Is history tracking required?

5. **Any known scale constraints?**
   - Expected row counts
   - Request volume (reads/writes per second)
   - Geographic distribution

### Usage
- Ask all questions before producing designs
- Document answers in design doc
- Use answers to inform indexing and denormalization decisions


Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…