Agent skill

Rating Prompt Strategy

When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period.

MITAuto-check passedMobile

Install Rating Prompt Strategy

skills CLI

$ npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install appeeky/aso-skills rating-prompt-strategy --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/appeeky/aso-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/rating-prompt-strategy .claude/skills/rating-prompt-strategy && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "rating-prompt-strategy" agent skill from https://github.com/appeeky/aso-skills/tree/main/skills/rating-prompt-strategy into .claude/skills/rating-prompt-strategy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rating-prompt-strategy", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/appeeky/aso-skills/tree/main/skills/rating-prompt-strategy

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install appeeky/aso-skills rating-prompt-strategy --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/appeeky/aso-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/rating-prompt-strategy .agents/skills/rating-prompt-strategy && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "rating-prompt-strategy" agent skill from https://github.com/appeeky/aso-skills/tree/main/skills/rating-prompt-strategy into .agents/skills/rating-prompt-strategy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rating-prompt-strategy", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install appeeky/aso-skills rating-prompt-strategy --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/appeeky/aso-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/rating-prompt-strategy .cursor/skills/rating-prompt-strategy && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "rating-prompt-strategy" agent skill from https://github.com/appeeky/aso-skills/tree/main/skills/rating-prompt-strategy into .cursor/skills/rating-prompt-strategy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rating-prompt-strategy", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/appeeky/aso-skills.git --path skills/rating-prompt-strategy

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install appeeky/aso-skills rating-prompt-strategy --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/appeeky/aso-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/rating-prompt-strategy .gemini/skills/rating-prompt-strategy && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "rating-prompt-strategy" agent skill from https://github.com/appeeky/aso-skills/tree/main/skills/rating-prompt-strategy into .gemini/skills/rating-prompt-strategy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rating-prompt-strategy", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install appeeky/aso-skills rating-prompt-strategy

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/appeeky/aso-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/rating-prompt-strategy .github/skills/rating-prompt-strategy && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "rating-prompt-strategy" agent skill from https://github.com/appeeky/aso-skills/tree/main/skills/rating-prompt-strategy into .github/skills/rating-prompt-strategy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rating-prompt-strategy", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install appeeky/aso-skills rating-prompt-strategy --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/appeeky/aso-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/rating-prompt-strategy .opencode/skills/rating-prompt-strategy && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "rating-prompt-strategy" agent skill from https://github.com/appeeky/aso-skills/tree/main/skills/rating-prompt-strategy into .opencode/skills/rating-prompt-strategy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rating-prompt-strategy", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: rating-prompt-strategy
GitHub stars: 2.2k
Token cost: ~1.6k tokens
SKILL.md length: 586 words
Files: 1
Skills in repo: 39
Repo updated: Oct 6, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period.

Works in 4 steps: Check which version caused the drop —… → Read the 1-star reviews for that period… → Fix the issue in the next release → …
Wants to improve their apps star rating
SKILL.md covers Why Ratings Matter for ASO, The Core Rule, iOS — SKStoreReviewRequest and Android — Play In-App Review API, plus 7 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Rating Prompt Strategy is an agent skill from appeeky/aso-skills. When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period. Use when the user mentions "app rating", "star rating", "review prompt", "SKStoreReviewRequest", "In-App Review API", "ask for review", "low rating", "rating drop", "get more reviews", or "recover from 1-star". For responding to reviews, see review-management. For overall ASO health, see aso-audit.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Mobile, covering App store release and Customer feedback analysis. It works with iOS. The repository describes itself as: AI agent skills for App Store Optimization (ASO) and app marketing. Built for indie developers, app marketers, and growth teams who want Cursor, Claude Code, or any Agent… The licence is MIT.

When your agent uses it

Wants to improve their apps star rating
Increase ratings volume
Optimize when and how they prompt users for a review
Recover from a bad rating period

Example prompts

“app rating”
“star rating”
“review prompt”
“/rating-prompt-strategy”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

Check which version caused the drop — correlate with release dates
Read the 1-star reviews for that period — find the common complaint
Fix the issue in the next release
Reply to every 1–3 star review (see review-management skill)

What it can do on your machine

Read from SKILL.md and the folder at commit 3919d7c. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are swift and kotlin).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Rating Prompt Strategy loads about 1.6k tokens when it runs. Until then it costs about 124 tokens; SKILL.md has 586 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~124
When it runs · the whole SKILL.md, loaded when a task matches: ~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from appeeky/aso-skills at commit 3919d7c, republished under its MIT licence (© appeeky). 586 words, ~1,638 tokens.

Download SKILL.mdSave it as .claude/skills/rating-prompt-strategy/SKILL.md (or your agent's skills folder).

name: rating-prompt-strategy
description: When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period. Use when the user mentions "app rating", "star rating", "review prompt", "SKStoreReviewRequest", "In-App Review API", "ask for review", "low rating", "rating drop", "get more reviews", or "recover from 1-star". For responding to reviews, see review-management. For overall ASO health, see aso-audit.
metadata.version: 1.0.0

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

swift

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)

kotlin

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

Session-Based Rules

Only prompt users who meet all criteria:

Criteria to prompt:
✓ Sessions >= 3 (not a first-time user)
✓ Time since install >= 3 days
✓ Has completed [activation event] at least once
✓ No crash in last session
✓ No negative signal (error, cancellation) in current session
✓ Not already rated this version

Pre-Prompt Survey (Recommended)

Before triggering the native prompt, show a single in-app question:

"Are you enjoying [App Name]?"
  [Yes, love it!]   [Not really]

"Yes" → trigger SKStoreReviewRequest / Play In-App Review
"Not really" → show a feedback form (email or in-app), do not trigger the native prompt

This filters out dissatisfied users before they can rate you 1–2 stars.

Expected improvement: 0.3–0.8 stars on average with a pre-prompt filter.

Show full SKILL.md (235 more words)Show less

Version-Gating (iOS)

iOS allows you to reset ratings per version in App Store Connect. Use this strategically:

Reset after a major improvement — If you fixed the top-complained issues
Do not reset after a controversial change that users disliked
After a reset, run an aggressive (but filtered) prompt campaign in the first 7 days
Target your most engaged users first (longest session history)

Recovering from a Rating Drop

Diagnosis

Check which version caused the drop — correlate with release dates
Read the 1-star reviews for that period — find the common complaint
Fix the issue in the next release
Reply to every 1–3 star review (see review-management skill)

Recovery Campaign

After the fix is shipped:

Reply to negative reviews: "Fixed in version X.X — please update and let us know"
Some users will update their rating after a reply
Run a prompt campaign targeted at your most loyal users (highest session count)
Do not prompt users who left a negative review

Timeline

Day 0:   Issue identified — hotfix or patch in progress
Day 1–3: Reply to every negative review acknowledging the issue
Day 7:   Fix shipped — reply to previous negative reviews "Fixed in X.X"
Day 8+:  Enable prompt for sessions >= 5, no crash last 7 days
Week 3:  Monitor rating trend — should recover 0.2–0.5 stars in 2–4 weeks

Prompt Frequency

Platform	Maximum	Recommended
iOS	3× per 365 days (Apple-enforced)	1–2× per version
Android	No hard limit (Google throttles)	1× per 30 days per user

Never show the prompt twice in the same session.

Output Format

Rating Strategy Plan

Current rating: [X.X] ★  ([N] ratings)
Platform: iOS / Android / Both

Success moments identified:
1. [Event name] — fires when [condition]
2. [Event name] — fires when [condition]

Pre-prompt survey: Yes / No
  If yes: "Are you enjoying [App Name]?" → Yes / Not really

Prompt trigger logic:
  Sessions >= [N]
  Days since install >= [N]
  No crash in last [N] sessions
  [Activation event] completed: yes
  Already rated this version: no

Expected outcome: +[X] stars over [N] weeks

Recovery plan (if rating < 4.0):
  1. [Fix] — ship by [date]
  2. [Reply strategy] — [N] reviews to address
  3. [Prompt campaign] — start [date], target [segment]

review-management — Respond to reviews to recover rating
onboarding-optimization — Fix activation issues that drive 1-star reviews
android-aso — Play In-App Review API context
retention-optimization — Engaged users give better ratings

Files

Just SKILL.md in skills/rating-prompt-strategy of appeeky/aso-skills.

Open the folder on GitHubat commit 3919d7c

Compare with similar skills

Rating Prompt Strategy next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Rating Prompt Strategy compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Rating Prompt Strategy this skillappeeky/aso-skills	2.2k	—	~1.6k	Automated safety check: Pass	MIT	4 days ago
Publish App Store VersionKeeForge/KeeForge	117	—	~3.5k	Automated safety check: Pass	GPL-3.0	today
Testflightkmworks/kmreader	113	—	~403	Automated safety check: Pass	MIT	today
Apple Guidelinesbpinheiroms/dotfiles	108	—	~14k	Automated safety check: Pass	None	4 mo ago
App Store Opportunity Researchrobertguss/claude-code-toolkit	124	—	~5.6k	Automated safety check: Pass	MIT	24 days ago
iOS Accessibilitydpearson2699/swift-ios-skills	1.2k	—	~4.6k	Automated safety check: Pass	Custom licence	2 mo ago

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Questions about Rating Prompt Strategy

What does Rating Prompt Strategy do?

When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period. Rating Prompt Strategy is an agent skill from appeeky/aso-skills. When the user wants to improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period.

When should I use Rating Prompt Strategy?

Rating Prompt Strategy fits situations like: wants to improve their apps star rating; increase ratings volume; optimize when and how they prompt users for a review; recover from a bad rating period.

How do I install Rating Prompt Strategy in Claude Code?

Run `npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a claude-code`. Or copy the skill folder (skills/rating-prompt-strategy in appeeky/aso-skills) into .claude/skills/rating-prompt-strategy in your project. Claude Code loads it when a task matches its description.

How do I install Rating Prompt Strategy in Codex?

Run `npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a codex`. Or copy the skill folder (skills/rating-prompt-strategy in appeeky/aso-skills) into .agents/skills/rating-prompt-strategy in your project. Codex loads it when a task matches its description.

Can I use Rating Prompt Strategy in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add appeeky/aso-skills --skill rating-prompt-strategy -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rating-prompt-strategy, .gemini/skills/rating-prompt-strategy, .github/skills/rating-prompt-strategy and .opencode/skills/rating-prompt-strategy in your project.

What does Rating Prompt Strategy need to run?

SKILL.md names no scripts, command-line tools or credentials: Rating Prompt Strategy is instructions for the agent only.

Does Rating Prompt Strategy access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Rating Prompt Strategy safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Rating Prompt Strategy use?

Rating Prompt Strategy is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Rating Prompt Strategy use?

About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Rating Prompt Strategy?

Skills that share tags, products or a category with Rating Prompt Strategy: Publish App Store Version (KeeForge/KeeForge, 117 stars), Testflight (kmworks/kmreader, 113 stars), Apple Guidelines (bpinheiroms/dotfiles, 108 stars) and App Store Opportunity Research (robertguss/claude-code-toolkit, 124 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Rating Prompt Strategy?

appeeky (a GitHub organization) maintains it in appeeky/aso-skills, which has 2,163 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on October 6, 2026.

Source: appeeky/aso-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Rating Prompt Strategy

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Rating Prompt Strategy

Why Ratings Matter for ASO

The Core Rule

iOS — SKStoreReviewRequest

Android — Play In-App Review API

Timing Framework

The Success Moment Trigger

Session-Based Rules

Pre-Prompt Survey (Recommended)

Version-Gating (iOS)

Recovering from a Rating Drop

Diagnosis

Recovery Campaign

Timeline

Prompt Frequency

Output Format

Rating Strategy Plan

Related Skills

Files

Compare with similar skills

Similar skills

More from appeeky/aso-skills

Related

Questions about Rating Prompt Strategy