lapsed-user

lapsed-user is a skill for Claude Code from rshankras/claude-code-apple-skills. It costs 49 tokens per session (2,377 once invoked), scanned A, original, MIT.

A generator for app flows that find inactive users and encourage them to return. A lapsed user is someone who has stopped opening an app for a defined period.

In plain words
What is it for?
Use it to build inactivity tracking, return screens that show what users missed, and win-back offers in Swift-based iOS or macOS apps.
Why use it?
It addresses user drop-off by identifying inactive users and showing them personalized return experiences or optional incentives.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool; positional $N argument.

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

Good fit Use it to build inactivity tracking, return screens that show what users missed, and win-back offers in Swift-based iOS or macOS apps.

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

README.md
[![agentmods](https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/lapsed-user/github.svg)](https://agentmods.dev/skills/rshankras/claude-code-apple-skills/lapsed-user)
Your own site
<a href="https://agentmods.dev/skills/rshankras/claude-code-apple-skills/lapsed-user"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/lapsed-user/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 lapsed-user

Your own site · 80×15
<a href="https://agentmods.dev/skills/rshankras/claude-code-apple-skills/lapsed-user"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/lapsed-user.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,377 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 $0.00049 $0.02377
Opus 5 $0.00024 $0.01189
Sonnet 5 $0.00010 $0.00475
Haiku 4.5 $0.00005 $0.00238

Measured 9d ago against content hash d7f57cb29083, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

lapsed-user 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 9d 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/lapsed-user/SKILL.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lapsed User Re-Engagement Generator

Generate production infrastructure for detecting users who haven't opened the app in X days, showing personalized return screens that highlight what they missed, and optionally presenting win-back incentives to recover churned or lapsing users.

When This Skill Activates

Use this skill when the user:

  • Asks about "lapsed user" detection or re-engagement
  • Wants to handle "returning user" or "inactive user" scenarios
  • Mentions "re-engagement" screens or flows
  • Asks about "win-back" offers for churned users
  • Wants to detect when a "user hasn't opened app" in a while
  • Asks about "user retention" or "come back" experiences

Pre-Generation Checks

1. Project Context Detection

  • Check Swift version (requires Swift 5.9+)
  • Check deployment target (iOS 17+ / macOS 14+ for @Observable)
  • Identify source file locations and project structure

2. Existing Engagement Tracking

Search for existing engagement or analytics infrastructure:

Glob: **/*Analytics*.swift, **/*Engagement*.swift, **/*Tracker*.swift, **/*Activity*.swift
Grep: "lastActiveDate" or "UserDefaults" or "scenePhase" or "applicationDidBecomeActive"

If existing tracking found:

  • Ask if user wants to integrate with it or build standalone
  • If integrating, adapt templates to use existing storage/events

3. Push Notification Setup

Search for existing push notification configuration:

Glob: **/*Notification*.swift, **/*Push*.swift
Grep: "UNUserNotificationCenter" or "UNNotification" or "registerForRemoteNotifications"

If push notifications are configured, offer push-based re-engagement as an option.

4. Conflict Detection

Search for existing lapsed user handling:

Glob: **/*LapsedUser*.swift, **/*WinBack*.swift, **/*ReturnExperience*.swift, **/*Reengag*.swift
Grep: "lapsedUser" or "winBack" or "returnExperience" or "daysInactive"

If existing implementation found:

  • Ask if user wants to replace or extend it
  • If extending, generate only the missing pieces

Read the full file on GitHub · 296 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 9d ago First seen · 296 lines · 49 tokens per session scan A d7f57cb29083

Subscribe to this mod's changes

lapsed-user is a skill published in the GitHub repository rshankras/claude-code-apple-skills (710 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 2,377 once invoked, about $0.0002 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 2026-08-30.

Related

Other skills, from other repositories

thinking-theory-of-constraints

When throughput or latency is pipeline-limited, identify the single binding constraint and exploit, subordinate, elevate, then recheck—ignore non-constraints.

tjboudreaux/cc-thinking-skills · 37 tokens

electron-desktop

Desktop application development with Electron for Windows, macOS, and Linux. Use when building cross-platform desktop apps, implementing native OS features, or packaging web apps for desktop.

travisjneuman/.claude · 38 tokens

impact-report-writer

Nonprofit/NGO impact report generation with data visualization suggestions, outcome metrics, narrative structure, and program data presentation. Use when writing impact reports, annual reports, or program evaluation summaries.

travisjneuman/.claude · 43 tokens

investment-memo-generator

Investment memo creation combining financial analysis, document generation, and structured templates. Use when creating investment memos, pitch decks, deal summaries, or investment committee materials.

travisjneuman/.claude · 37 tokens

generic-static-feature-developer

Guide feature development for static HTML/CSS/JS sites. Covers patterns, automation workflows, and content validation. Use when adding features, modifying automation, or planning changes.

travisjneuman/.claude · 40 tokens

python-memory-safe-scripts

Memory-safe Python script patterns for long-running processes under systemd MemoryMax constraints. Covers allocator purge (mimalloc/glibc malloctrim), HTTP response lifecycle, DataFrame cleanup, thread-local connection reuse, and periodic GC cadence. Battle-tested through 5 OOM optimization cycles on production GPU…

terrylica/cc-skills · 197 tokens