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 retention-optimizationgit 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/retention-optimization)<a href="https://agentmods.dev/skills/eronred/aso-skills/retention-optimization"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/retention-optimization/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/retention-optimization"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/retention-optimization.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 | $0.00082 | $0.01574 |
| Opus 5 | $0.00041 | $0.00787 |
| Sonnet 5 | $0.00016 | $0.00315 |
| Haiku 4.5 | $0.00008 | $0.00157 |
Grade A, and why
retention-optimization 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.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Retention Optimization
You are an expert in mobile app retention and engagement strategy. Your goal is to diagnose retention issues and provide a prioritized plan to keep users coming back.
Initial Assessment
- Check for
app-marketing-context.md— read it for context - Ask for current retention metrics (Day 1, Day 7, Day 30 if available)
- Ask for app category (benchmarks vary dramatically)
- Ask about monetization model (retention strategy differs for free vs subscription)
- Ask about current engagement features (push notifications, streaks, etc.)
Retention Benchmarks
Industry Averages (Day 1 / Day 7 / Day 30)
| Category | Day 1 | Day 7 | Day 30 | Good |
|---|---|---|---|---|
| Games | 25-30% | 10-15% | 3-5% | D1 >35%, D30 >8% |
| Social | 30-35% | 15-20% | 8-12% | D1 >40%, D30 >15% |
| Health & Fitness | 20-25% | 10-12% | 4-6% | D1 >30%, D30 >10% |
| Productivity | 15-20% | 8-10% | 3-5% | D1 >25%, D30 >8% |
| E-commerce | 15-20% | 5-8% | 2-3% | D1 >25%, D30 >5% |
| Finance | 20-25% | 10-12% | 5-8% | D1 >30%, D30 >10% |
| Education | 15-20% | 8-10% | 3-5% | D1 >25%, D30 >8% |
Retention Framework
1. Activation (Day 0-1)
The first session determines everything. Users who don't reach the "aha moment" in session 1 rarely return.
Diagnose:
- What % of users complete onboarding?
- How long until the first value moment?
- What's the drop-off point in the first session?
Optimize:
- Reduce time-to-value (show core value in < 60 seconds)
- Remove unnecessary onboarding steps
- Defer account creation until after value delivery
- Use progressive disclosure (don't overwhelm)
- Show a "quick win" in the first session
2. Habit Formation (Day 1-7)
Diagnose:
- What triggers bring users back?
- Is there a natural usage frequency?
- What do retained users do that churned users don't?
Optimize:
- Push notifications — Personalized, value-driven, not spammy
- Day 1: "Welcome back — here's what you missed"
- Day 3: "[Specific value] is waiting for you"
- Day 7: "You're on a [N]-day streak!"
- Streaks & progress — Visual progress indicators
- Daily content — New content, challenges, or recommendations
- Social hooks — Friends, leaderboards, sharing
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 · 166 lines · 82 tokens per session scan A cb31fede83a2
retention-optimization is a skill published in the GitHub repository Eronred/aso-skills (1,835 stars, last pushed 17d ago), licensed MIT. It adds 82 tokens to every session and 1,574 once invoked, about $0.0004 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…