rating-prompt-strategy

rating-prompt-strategy is a skill for Claude Code from Eronred/aso-skills. It costs 116 tokens per session (1,572 once invoked), scanned A, original, MIT.

An HTTP interface for controlling a browser and reading or changing web pages. It supports navigation, clicking, typing, selecting options, data extraction, accessibility inspection, screenshots, and JavaScript execution.

In plain words
What is it for?
Use it to build browser workflows, interact with page elements, collect text or attributes, inspect page structure, run page scripts, and take screenshots.
Why use it?
It lets software automate browser work through requests instead of requiring a person to operate the browser manually. Batch operations can also run several browser actions in sequence.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the aso-skills plugin — 40 skills shipped together

Good fit Use it to build browser workflows, interact with page elements, collect text or attributes, inspect page structure, run page scripts, and take screenshots.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/eronred/aso-skills/rating-prompt-strategy
About the project

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.

Eronred/aso-skills · 1,851 stars · on GitHub · appeeky.com

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 Eronred/aso-skills --skill rating-prompt-strategy
Clone the repo
git clone --depth 1 https://github.com/Eronred/aso-skills

Made for: Claude Code.

Or install aso-skills, the plugin that ships this one along with the rest of its 40 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 rating-prompt-strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/eronred/aso-skills/rating-prompt-strategy/github.svg)](https://agentmods.dev/skills/eronred/aso-skills/rating-prompt-strategy)
Your own site
<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.

agentmods 80×15 button for rating-prompt-strategy

Your own site · 80×15
<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>
Per session 116 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,572 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
  • Socket pass 22 Mar 2026
  • Snyk warn 22 Mar 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
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.
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 $0.00116 $0.01572
Opus 5 $0.00058 $0.00786
Sonnet 5 $0.00023 $0.00314
Haiku 4.5 $0.00012 $0.00157

Measured 12d ago against content hash e40e57f2036e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

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.

skills/rating-prompt-strategy/SKILL.md · 185 lines

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

Read the full file on GitHub · 185 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. 12d ago First seen · 185 lines · 116 tokens per session scan A e40e57f2036e

Subscribe to this mod's changes

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.

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