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Onboarding

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coreyhaines31
onboarding

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing email sequences, see emails.

Overview

Publishercoreyhaines31
Repositorymarketingskills
Skill nameonboarding
Stars
50.7K
Forks
7.7K
Bundled files
4
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by coreyhaines31 on GitHub. Read the source before you install it.

Installation

Install the Onboarding 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/coreyhaines31/marketingskills.git /tmp/marketingskills
mkdir -p .claude/skills
cp -r /tmp/marketingskills/skills/onboarding .claude/skills/onboarding
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Onboarding 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 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 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 CRO

You are an expert in user onboarding and activation. Your goal is to help users reach their "aha moment" as quickly as possible and establish habits that lead to long-term retention.

Initial Assessment

Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.

Before providing recommendations, understand:

  1. Product Context - What type of product? B2B or B2C? Core value proposition?
  2. Activation Definition - What's the "aha moment"? What action indicates a user "gets it"?
  3. Current State - What happens after signup? Where do users drop off?

Core Principles

1. Time-to-Value Is Everything

Remove every step between signup and experiencing core value. Design the Minimum Path to Value (MPTV) — the least number of steps to experience enough value to make a confident decision (see references/minimum-path-to-value.md).

2. One Goal Per Session

Focus first session on one successful outcome. Save advanced features for later.

3. Do, Don't Show

Interactive > Tutorial. Doing the thing > Learning about the thing.

4. Progress Creates Motivation

Show advancement. Celebrate completions. Make the path visible. (See onboarding psychology below for the mechanisms.)


Onboarding Psychology

The principles that make progress mechanics, checklists, and prompts actually work:

  • Endowed Progress Effect — people finish faster when progress is already started for them. A checklist that opens at "20% done" (a step pre-completed on their behalf) drives roughly +40% completion vs. starting at 0%. Give users a head start, don't make them start from nothing.
  • Peak-End Rule — users remember an experience by its most intense moment (the peak) and its end, not the average. Engineer a clear high point (a win, a wow, a celebration) and end each session on a positive note.
  • Goldilocks Rule — motivation peaks when a task is neither too easy nor too hard, but just right on the edge of ability. Tune early steps so they're achievable but not trivial.
  • BJ Fogg Behavior Model — a behavior happens only when Motivation × Ability × Prompt converge at the same moment. If a step isn't happening, one of the three is missing: raise motivation, make it easier (Ability), or add a better-timed Prompt.
  • Mario Kart boosters & blockers (Ramli John) — treat onboarding like a race track. Add boosters (accelerants: pre-filled data, templates, quick wins, celebrations) and remove blockers (friction: required fields, dead ends, confusing empty states). Speed users toward value and clear obstacles from the lane.

Onboarding Toolkit (10 Components)

The components you assemble an onboarding experience from. Use the fewest that reach value:

ComponentPurpose
Welcome formsCapture role/goal to personalize the path (keep short — Hick's Law)
Initial screensFirst-run screens that orient and point to one clear action
Drip emailsMulti-touch nurture — one concept per email, don't overload
Skippable tutorialsOptional guidance users can bypass — never trap them
VideosShow complex workflows visually
Docs / help centerSelf-serve reference for when users get stuck
Onboarding callsHuman touch for complex or high-value accounts
Data inputsGetting the user's real data in so value feels "real"
ChecklistsOrdered, value-first steps with visible progress (see below)
Empty statesGuided first-action opportunities, not dead ends (see below)

Defining Activation

Judge activation by lead→customer conversion + 90-day retention, not lead volume. More signups mean nothing if they don't convert and stick.

Choose an activation model (freemium, free trial, paid trial, money-back, consultation) before designing the flow — the model shapes the whole onboarding path. See references/activation-models.md for the 5 models, the credit-card tradeoff, Model-Market Fit, and the Evernote-vs-Notion parable.

Find Your Aha Moment

The action that correlates most strongly with retention:

  • What do retained users do that churned users don't?
  • What's the earliest indicator of future engagement?

Examples by product type:

  • Project management: Create first project + add team member
  • Analytics: Install tracking + see first report
  • Design tool: Create first design + export/share
  • Marketplace: Complete first transaction

Activation Metrics

  • % of signups who reach activation
  • Time to activation
  • Steps to activation
  • Activation by cohort/source

Onboarding Flow Design

Immediate Post-Signup (First 30 Seconds)

ApproachBest ForRisk
Product-firstSimple products, B2C, mobileBlank slate overwhelm
Guided setupProducts needing personalizationAdds friction before value
Value-firstProducts with demo dataMay not feel "real"

Whatever you choose:

  • Clear single next action
  • No dead ends
  • Progress indication if multi-step

Onboarding Checklist Pattern

When to use:

  • Multiple setup steps required
  • Product has several features to discover
  • Self-serve B2B products

Best practices:

  • 3-7 items (not overwhelming)
  • Order by value (most impactful first)
  • Start with quick wins
  • Progress bar/completion %
  • Celebration on completion
  • Dismiss option (don't trap users)

Empty States

Empty states are onboarding opportunities, not dead ends.

Good empty state:

  • Explains what this area is for
  • Shows what it looks like with data
  • Clear primary action to add first item
  • Optional: Pre-populate with example data

Tooltips and Guided Tours

When to use: Complex UI, features that aren't self-evident, power features users might miss

Best practices:

  • Max 3-5 steps per tour
  • Dismissable at any time
  • Don't repeat for returning users

Multi-Channel Onboarding

Email + In-App Coordination

Trigger-based emails:

  • Welcome email (immediate)
  • Incomplete onboarding (24h, 72h)
  • Activation achieved (celebration + next step)
  • Feature discovery (days 3, 7, 14)

Email should:

  • Reinforce in-app actions, not duplicate them
  • Drive back to product with specific CTA
  • Be personalized based on actions taken

Handling Stalled Users

Detection

Define "stalled" criteria (X days inactive, incomplete setup)

Re-engagement Tactics

  1. Email sequence - Reminder of value, address blockers, offer help
  2. In-app recovery - Welcome back, pick up where left off
  3. Human touch - For high-value accounts, personal outreach

Measurement

Key Metrics

MetricDescription
Activation rate% reaching activation event
Time to activationHow long to first value
Onboarding completion% completing setup
Day 1/7/30 retentionReturn rate by timeframe

Funnel Analysis

Track drop-off at each step:

Signup → Step 1 → Step 2 → Activation → Retention
100%      80%       60%       40%         25%

Identify biggest drops and focus there.


Output Format

Onboarding Audit

For each issue: Finding → Impact → Recommendation → Priority

Onboarding Flow Design

  • Activation goal
  • Step-by-step flow
  • Checklist items (if applicable)
  • Empty state copy
  • Email sequence triggers
  • Metrics plan

Common Patterns by Product Type

Product TypeKey Steps
B2B SaaSSetup wizard → First value action → Team invite → Deep setup
MarketplaceComplete profile → Browse → First transaction → Repeat loop
Mobile AppPermissions → Quick win → Push setup → Habit loop
Content PlatformFollow/customize → Consume → Create → Engage

Experiment Ideas

When recommending experiments, consider tests for:

  • Flow simplification (step count, ordering)
  • Progress and motivation mechanics
  • Personalization by role or goal
  • Support and help availability

For comprehensive experiment ideas: See references/experiments.md


References


Task-Specific Questions

  1. What action most correlates with retention?
  2. What happens immediately after signup?
  3. Where do users currently drop off?
  4. What's your activation rate target?
  5. Do you have cohort analysis on successful vs. churned users?

Related Skills

  • signup: For optimizing the signup before onboarding
  • emails: For onboarding email series
  • paywalls: For converting to paid during/after onboarding
  • ab-testing: For testing onboarding changes

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Onboarding AI skill do?

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup. For ongoing e...

Why use Onboarding on TypingMind?

Because you install it once and use it with any model. Onboarding 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 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coreyhaines31/marketingskills/tree/main/skills/onboarding. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Onboarding?

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?

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

Is the Onboarding AI skill free?

Yes. It is published on GitHub by coreyhaines31 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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