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 rating-prompt-strategygit 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/rating-prompt-strategy)<a href="https://agentmods.dev/skills/eronred/aso-skills/rating-prompt-strategy"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/rating-prompt-strategy/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/rating-prompt-strategy"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/rating-prompt-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 128 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00116 | $0.01572 |
| Opus 5 | $0.00058 | $0.00786 |
| Sonnet 5 | $0.00023 | $0.00314 |
| Haiku 4.5 | $0.00012 | $0.00157 |
Grade A, and why
rating-prompt-strategy 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 12d 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 — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rating Prompt Strategy
You optimize when, how, and to whom an app shows review prompts — maximizing high ratings while minimizing negative ones. Ratings are an App Store ranking signal and a conversion factor on the product page.
Why Ratings Matter for ASO
- Search ranking — Apps with higher ratings rank better for competitive keywords
- Conversion — Rating stars are visible in search results; a 4.8 beats 4.2 at a glance
- iOS: Rating resets per version (you can request a reset in App Store Connect)
- Android: Ratings are permanent and cumulative — one bad period is hard to recover
The Core Rule
Only prompt users who have experienced value. Prompting too early produces low ratings. Prompting at a success moment produces 4–5 star ratings.
iOS — SKStoreReviewRequest
Apple's native prompt. Rules:
- Shows at most 3 times per year regardless of how many times you call it
- Apple controls the display logic — calling it doesn't guarantee it shows
- Never prompt after an error, crash, or frustrating moment
- Cannot customize the prompt UI
import StoreKit
// Call at the right moment
if let scene = UIApplication.shared.connectedScenes.first as? UIWindowScene {
SKStoreReviewController.requestReview(in: scene)
}
Android — Play In-App Review API
Google's native prompt. Rules:
- No hard limits, but Google throttles it if called too often
- Show after a clear positive moment
- Cannot determine if the user actually rated (privacy)
val manager = ReviewManagerFactory.create(context)
val request = manager.requestReviewFlow()
request.addOnCompleteListener { task ->
if (task.isSuccessful) {
val reviewInfo = task.result
val flow = manager.launchReviewFlow(activity, reviewInfo)
flow.addOnCompleteListener { /* proceed */ }
}
}
Timing Framework
The Success Moment Trigger
Define 1–3 "success moments" in your app where users are most satisfied:
| App Type | Good Prompt Moments | Bad Prompt Moments |
|---|---|---|
| Fitness | After completing a workout | After skipping a session |
| Productivity | After completing a project/task | After a failed save or sync error |
| Games | After winning a level or beating a boss | After losing or failing |
| Finance | After first successful transaction | After a confusing error |
| Meditation | After completing a session | On cold open |
| Shopping | After a successful purchase/delivery | After a failed checkout |
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.
- 12d ago First seen · 185 lines · 116 tokens per session scan A e40e57f2036e
rating-prompt-strategy is a skill published in the GitHub repository Eronred/aso-skills (1,851 stars, last pushed 20d ago), licensed MIT. It adds 116 tokens to every session and 1,572 once invoked, about $0.0006 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…