AGENT SKILLBY ERONRED
Rating prompt strategy
AT A GLANCE
Rating prompt strategy is a go-to-market agent skill from eronred. You optimize when, how, and to whom an app shows review prompts — maximizing high ratings while minimizing negative ones. The eronred/aso-skills repository on GitHub has 1.6K stars and the MIT license. To add it, run npx skills add eronred/aso-skills --skill rating-prompt-strategy
- SOURCE REPOSITORY
- eronred/aso-skills (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 5.9 KB178 LINES
QUICK ANSWER
- WHAT IT IS01
- You optimize when, how, and to whom an app shows review prompts, maximizing high ratings while minimizing negative ones. What sets it apart is how it narrows rating prompt strategy into one specific workflow rather than a broad, generic prompt.
- INPUTS02
- Context the agent needs: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result: the analysis, copy, or recommendations the agent produces.
INSTALL
One command adds this skill from its source repository.
npx skills add eronred/aso-skills --skill rating-prompt-strategyREAD THE SKILL.MD BELOW BEFORE YOU RUN IT. SKILLS INSTRUCT YOUR AGENT.
SKILL.MD
The full file, as published in the source repository. Copy it, download it or open it on GitHub.
ON THIS PAGE · 17
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 |
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 versionPre-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.
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-managementskill)
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 weeksPrompt 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]Related Skills#
review-management— Respond to reviews to recover ratingonboarding-optimization— Fix activation issues that drive 1-star reviewsandroid-aso— Play In-App Review API contextretention-optimization— Engaged users give better ratings
FAQ
07 QUESTIONS
01What is the Rating prompt strategy agent skill?
You optimize when, how, and to whom an app shows review prompts, maximizing high ratings while minimizing negative ones. It is listed under go-to-market in the 100xLab agent skills directory.
02How do I install Rating prompt strategy in Cursor, Claude Code, or Codex?
Run npx skills add eronred/aso-skills --skill rating-prompt-strategy in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Rating prompt strategy, not every skill in the repository.
03What does the Rating prompt strategy SKILL.md cover?
The SKILL.md includes sections on Why Ratings Matter for ASO, The Core Rule, iOS — SKStoreReviewRequest, Android — Play In-App Review API, Timing Framework and The Success Moment Trigger. Read the full text on this page or in plain markdown at /resources/agent-skills/eronred-aso-skills--rating-prompt-strategy--ax8q1j/raw.
04Which agents can use Rating prompt strategy?
Rating prompt strategy installs with the cross-agent skills installer (npx skills add), which sets it up for agents such as Claude Code, Cursor and Codex. Each agent loads the SKILL.md when you ask for the skill by name.
05What license is Rating prompt strategy under?
The eronred/aso-skills repository declares the MIT license. Read the license file in the repository before you copy or redistribute the skill.
06Is Rating prompt strategy free to use?
Reading, copying and installing Rating prompt strategy costs nothing: it is published in a public GitHub repository under the MIT license. Reuse and redistribution follow that license.
07Where is the source of Rating prompt strategy?
Rating prompt strategy comes from https://github.com/eronred/aso-skills, which has 1.6K GitHub stars. The SKILL.md is at https://github.com/eronred/aso-skills/blob/HEAD/skills/rating-prompt-strategy/SKILL.md. The author is eronred.
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ATTRIBUTION
Rating prompt strategy was written by its original authors and is published in eronred/aso-skills (opens GitHub in a new tab) under the MIT license. All rights stay with the original authors.
100xLab did not write, maintain or endorse this skill. This page lists it for discovery. Repo stars belong to the source repository, not to the skill. Review any skill before you install it.