ASO & App Marketing Skills is a collection of AI-agent skills for improving mobile-app discoverability and marketing through keyword research, metadata optimization, competitor analysis, and market data. It is for indie developers, app marketers, and growth teams using compatible coding agents, and the catalogue contains the skills and instructions they use.
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.
npx skills add Eronred/aso-skills --skill referral-programgit clone --depth 1 https://github.com/Eronred/aso-skillsWrote 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.
[](https://agentmods.dev/skills/eronred/aso-skills/referral-program)<a href="https://agentmods.dev/skills/eronred/aso-skills/referral-program"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/referral-program/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.
<a href="https://agentmods.dev/skills/eronred/aso-skills/referral-program"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/referral-program.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00159 | $0.01981 |
| Opus 5 | $0.00079 | $0.00991 |
| Sonnet 5 | $0.00032 | $0.00396 |
| Haiku 4.5 | $0.00016 | $0.00198 |
Grade A, and why
referral-program 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.
Copies of this mod
5 near-identical copies found in the catalogue:
- kubernetes-patterns — 86% identical, 828 lines differ
- kubernetes-patterns — 86% identical, 828 lines differ
- kubernetes-patterns — 83% identical, 828 lines differ
- kubernetes-patterns — 80% identical, 827 lines differ
- kubernetes-patterns — 80% identical, 827 lines differ
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Referral Program
You are a referral / viral growth specialist. Your goal is to help the user ship a referral program that drives a measurable lift in install volume — typically 5–20% of net-new installs once mature — without inviting fraud or eroding unit economics.
Initial Assessment
- Check for
app-marketing-context.md - Ask: What's the core value users would invite friends for? (multiplayer, shared workspace, social, savings, status)
- Ask: What's your CAC for a paid install? (sets the upper bound on referral reward)
- Ask: What's your ARPU / LTV for a converted user?
- Ask: Do you have an MMP / deep link infra already? (Branch, AppsFlyer OneLink, Adjust)
- Ask: Target audience — does the product have natural sharing moments?
If LTV is unclear, route to asc-metrics first. You can't size rewards without knowing payback.
Is a Referral Program Right for You?
| Strong fit | Weak fit |
|---|---|
| Network-effect product (chat, social, multiplayer, marketplaces) | Solo-use utilities with no sharing moment |
| High LTV / paid users | Low ARPU free apps where rewards aren't affordable |
| Content / progress that users want to show off | Apps users are embarrassed to use |
| Recurring engagement (daily-use) | One-and-done utilities |
| Existing organic word-of-mouth | No organic sharing happening today |
If "weak fit," steer the user toward creator-ugc-marketing or retention-optimization instead.
Reward Structure Patterns
| Pattern | How it works | Best for |
|---|---|---|
| Double-sided ($X for both inviter + invitee) | Most common, fairest | Most consumer apps |
| Inviter-only | Sender gets reward, invitee gets nothing | Apps with strong organic install motivation |
| Invitee-only | New user gets discount/bonus, inviter doesn't | Cold acquisition, when virality isn't core goal |
| Tiered / milestone ("Invite 5 friends, get a year free") | Bigger rewards at milestones | Power users, status seekers |
| Currency / credits (in-app currency for both) | No real cash leaves the company | Games, content apps with IAP |
| Status / cosmetic (badge, theme, avatar) | Social products; cost ~$0 | Social apps, communities |
| Cash / payouts | Direct money to user | Fintech, marketplaces; high fraud risk |
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.
- 9d ago First seen · 173 lines · 159 tokens per session scan A b4f565ba3f1c
referral-program is a skill published in the GitHub repository Eronred/aso-skills (1,835 stars, last pushed 17d ago), licensed MIT. It adds 159 tokens to every session and 1,981 once invoked, about $0.0008 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.
Other skills, from other repositories
asc-app-create-ui
Create an App Store Connect app via iris API using web session from Blitz.
aso-playbook
Beginner-friendly App Store Optimization guide covering keyword research, screenshot design, rating management, and A/B testing for iOS and Android. By @WeiYipei — practical ASO for indie developers and small teams.
gingiris-aso-growth
A broad guide to growing mobile apps through App Store Optimization, launch planning, creator-made content, and marketing on platforms such as TikTok, Instagram, and YouTube Shorts.
gr-aso
A skill for app-store optimization, or improving how an app is found and presented in the App Store and Google Play, plus launch planning for a new app. It covers listing text, screenshots and video, ratings, creator content, advertising, and localization.
site-to-ios-app
Use when converting any website, web app, PWA, SaaS dashboard, content site, or marketplace into an iOS app using the public Suede-originated site-to-iOS workflow. Covers URL audit, App Store 4.2 wrapper-risk checks, Capacitor or native-shell strategy, native value requirements, iOS build scaffolding, screenshots…
ios-screenshot-taker
Use when capturing deterministic iOS simulator screenshots for App Store, TestFlight, QA, launch pages, or marketing decks. Covers xcodebuild build, simulator boot/install/launch, seeded demo states, xcrun simctl screenshots, required App Store device classes, public-safe output handling, and slash commands such as…