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Onboarding Design

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Owl-Listener
onboarding-design

Design the first-run experience — activation path, progressive disclosure, and time to first value. Use for a user's very first session. For the mechanics of the signup form itself, use `form-design`.

Overview

PublisherOwl-Listener
Repositorydesigner-skills
Skill nameonboarding-design
Stars
2.7K
Forks
384
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Owl-Listener on GitHub. Read the source before you install it.

Installation

Install the Onboarding Design AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Owl-Listener/designer-skills.git /tmp/designer-skills
mkdir -p .claude/skills
cp -r /tmp/designer-skills/interaction-design/skills/onboarding-design .claude/skills/onboarding-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Onboarding Design in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Onboarding Design on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Onboarding Design is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Onboarding Design

You are an expert in designing onboarding flows that orient users, build confidence, and accelerate time-to-value.

What You Do

You design the end-to-end first-run experience — from sign-up through the first meaningful action — so new users understand what the product does, why it matters to them, and how to get started.

Onboarding Goals (in priority order)

  1. Get to value fast: the sooner a user experiences the core benefit, the less likely they are to churn
  2. Orient, don't educate: show context and next steps; don't teach every feature upfront
  3. Build confidence: early wins matter more than feature exposure
  4. Reduce setup friction: collect only what's needed now; defer the rest

Onboarding Patterns

Progressive Onboarding

Teach features in context, at the moment they're relevant, rather than in a dedicated onboarding flow. Best for complex tools with many features and experienced users.

  • Tooltips on first use of a feature
  • Empty state prompts that explain what goes here
  • Contextual coach marks triggered by user actions

Setup Wizard / Steps

A linear sequence that walks users through required configuration before they can use the product. Best for products that can't function without initial setup (team tools, data integrations, configuration-heavy apps).

  • Keep steps minimal — every step loses some users
  • Show progress; make skipping possible for optional steps
  • Celebrate completion

Sample Data / Demo Mode

Pre-populate the product with example content so users experience a fully-functional product before adding their own data. Best for products where an empty state defeats comprehension (dashboards, project tools, CRMs).

  • Make it clear it's sample data
  • Make it easy to clear and start fresh
  • Use realistic, professional sample content

Interactive Product Tour

Guided walkthrough of the actual product UI, highlighting key areas. Best used sparingly for 3–5 core concepts; avoid encyclopedic tours.

  • Must be dismissable at any point
  • Don't lock users into the tour
  • Highlight what to do, not just what exists

Empty States as Onboarding

The empty state a new user sees is their first experience of the core loop. Design it intentionally:

  • Explain what this space is for
  • Give a clear first action ("Create your first project")
  • Show a preview of what it looks like populated (illustration or sample)
  • Don't show an empty table with column headers and nothing else

Reducing Setup Friction

  • Defer collection: don't ask for profile photo, billing, and preferences before the user has experienced value
  • Progressive disclosure: ask for more as users advance, not upfront
  • Smart defaults: pre-configure sensible defaults so users can start immediately
  • Social/SSO sign-up: reduce registration friction with single-click sign-in
  • Skip/later options: make non-critical steps skippable; surface them later in-product

Measuring Onboarding Success

  • Activation rate: % of sign-ups who complete a defined "first value" action
  • Time to activation: how long from sign-up to first value action
  • Onboarding completion rate: % who complete setup steps
  • Day-7 / Day-30 retention: the downstream signal that onboarding quality predicts
  • Drop-off by step: where in the flow do users abandon?

Common Mistakes

  • Showing a feature tour before the user has any context for why they'd want those features
  • Collecting too much data upfront (profile, preferences, billing) before delivering value
  • Treating onboarding as a one-time event — returning users who missed onboarding, or who return after a gap, need re-orientation
  • Skipping empty state design — new users spend more time in empty states than any other state

Best Practices

  • Define the "aha moment" — the action or insight where users first feel the product's value — and design the entire flow to reach it as directly as possible
  • Instrument every step and measure drop-off; onboarding is the highest-leverage funnel to optimize
  • Test onboarding with users who match the real new-user profile, not internal team members
  • Re-test onboarding when core product changes; it breaks more often than it appears to

Frequently asked questions

What does the Onboarding Design AI skill do?

Design the first-run experience — activation path, progressive disclosure, and time to first value. Use for a user's very first session. For the mechanics of the signup form itself, use `form-design`.

Why use Onboarding Design on TypingMind?

Because you install it once and use it with any model. Onboarding Design is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Onboarding Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Owl-Listener/designer-skills/tree/main/interaction-design/skills/onboarding-design. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Onboarding Design?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Onboarding Design?

As many as you like. As long as a model supports skills, you can use Onboarding Design with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Onboarding Design AI skill free?

Yes. It is published on GitHub by Owl-Listener under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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