# Design Onboarding Mental Model

> Design onboarding, first-run experiences, walkthroughs, empty states, product explainers, training flows, explainer decks, educational PDFs, and feature introductions around accurate user mental models. Use when Codex needs to help new users understand what something is, how it works, why it matters, what to do first, or how to update an incorrect expectation.

- Skill: `amaledtuning/design-onboarding-mental-model` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add amaledtuning/design-onboarding-mental-model`
- Raw SKILL.md: https://api.skillmd.com/api/skills/amaledtuning/design-onboarding-mental-model/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: amaledtuning (https://skillmd.com/u/amaledtuning)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/amaledtuning/design-onboarding-mental-model

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# Design Onboarding Mental Model

Use this skill when the problem is not just readability but understanding: the user needs a correct mental model of a product, workflow, concept, or feature. It applies to onboarding UI, first-run flows, empty states, feature announcements, pitch/explainer decks, PDF guides, diagrams, and tutorial visuals.

## Workflow

1. Identify the user's likely existing mental model and where it differs from the intended conceptual model.
2. Read `references/principles.md` when designing onboarding, walkthroughs, empty states, explainers, educational decks/PDFs, or feature introductions.
3. Define the first useful action, the core concept to teach, and the minimum vocabulary the user needs.
4. Teach through concrete examples, narrative sequence, progressive disclosure, and visible cause-effect feedback.
5. Pair with execution skills as needed: `frontend-design`, `presentations`, `documents`, `imagegen`, `figma`, or `react`.

## Output Expectations

Return an onboarding or explanation structure that states what the user believes, what they need to believe instead, what proof or example teaches it, and what first action confirms learning.

## Boundaries

Do not use this skill for ordinary text cleanup without a mental-model problem. Use `improve-readability-information-design` for wording and layout, and `reduce-cognitive-load` for memory/complexity reduction inside an already understood workflow.