onboarding-generator

onboarding-generator is a skill for Claude Code from rshankras/claude-code-apple-skills. It costs 93 tokens per session (4,025 once invoked), scanned A, original, MIT.

A generator for first-run app experiences that guide users to the app's promised result. It can choose a short path for users ready to act or save a plan for users who are not ready yet.

In plain words
What is it for?
Use it to build onboarding, welcome screens, first-launch tutorials, and post-signup or post-purchase activation flows for iOS and macOS apps.
Why use it?
It helps new users reach a useful outcome instead of only reading through introductory screens. It also provides a fallback for apps that genuinely need a traditional welcome tour.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the apple-skills plugin — 147 skills shipped together , and of apple-skills

Good fit Use it to build onboarding, welcome screens, first-launch tutorials, and post-signup or post-purchase activation flows for iOS and macOS apps.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/rshankras/claude-code-apple-skills/onboarding-generator
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add rshankras/claude-code-apple-skills --skill onboarding-generator
Clone the repo
git clone --depth 1 https://github.com/rshankras/claude-code-apple-skills

Made for: Claude Code.

Or install apple-skills, the plugin that ships this one along with the rest of its 147 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for onboarding-generator

README.md
[![agentmods](https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/onboarding-generator/github.svg)](https://agentmods.dev/skills/rshankras/claude-code-apple-skills/onboarding-generator)
Your own site
<a href="https://agentmods.dev/skills/rshankras/claude-code-apple-skills/onboarding-generator"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/onboarding-generator/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for onboarding-generator

Your own site · 80×15
<a href="https://agentmods.dev/skills/rshankras/claude-code-apple-skills/onboarding-generator"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/onboarding-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,025 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00093 $0.04025
Opus 5 $0.00046 $0.02013
Sonnet 5 $0.00019 $0.00805
Haiku 4.5 $0.00009 $0.00402

Measured 7d ago against content hash 55254bffa39e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

onboarding-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/generators/onboarding-generator/SKILL.md · 293 lines

How it starts

The opening of the file, as written. The whole thing — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Onboarding Generator

Generate onboarding whose job is to get a new user to the value moment — the first time they experience (never just read about) the outcome the app promises — as fast as their situation allows.

Default architecture: value-moment-first, branching on readiness. The user answers one question ("can you do this right now?"), and the path is either the shortest possible route to the value moment, or a captured plan to reach it later. Fallback architecture: the classic paged welcome carousel — generate it only when Step 0 below confirms the app is genuinely explain-first.

Read onboarding-patterns.md for the full philosophy, the nine implementation lessons (each with a code sketch), and a worked case study.

When This Skill Activates

Use this skill when the user:

  • Asks to "add onboarding" or "create onboarding"
  • Mentions "welcome screens" or "first launch"
  • Wants to "show intro on first launch"
  • Asks about "onboarding flow" or "tutorial screens"
  • Wants to improve "activation," "time-to-value," or "trial conversion"
  • Asks "why do users churn right after signup/purchase" (post-purchase first-run is half of this skill)

Before Anything Else: What Is The Value Moment?

This is the question that decides every downstream choice — ask it before any configuration question. If the requester can't answer it, help them find it: it's the first specific instant a user feels the outcome, not a feature list. "Sees a demo of X" is not a value moment; "actually did X and saw the result" is.

Onboarding that ends before the user felt the value moment didn't finish — it just stopped.

Pre-Generation Checks

1. Project Context Detection

  • Check deployment target (@Observable needs iOS 17+/macOS 14+; fall back to ObservableObject below that)
  • Identify the app's core feature and its existing entry point — the value moment almost always lives inside a feature that already exists (or is being built alongside this flow); this skill wires into it, it does not rebuild it (see onboarding-patterns.md Lesson 3)
  • Check whether the app has a launch paywall (Glob: **/*Paywall*.swift, **/*StoreKit*.swift, or an installed generators/paywall-generator output) — determines free-first vs paywalled-first in Configuration Question 2
  • Check for UNUserNotificationCenter usage already in the project — reuse the existing permission seam if one exists rather than creating a second

Read the full file on GitHub · 293 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 293 lines · 93 tokens per session scan A 55254bffa39e

Subscribe to this mod's changes

onboarding-generator is a skill published in the GitHub repository rshankras/claude-code-apple-skills (713 stars, last pushed 1mo ago), licensed MIT. It adds 93 tokens to every session and 4,025 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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