agentsclimarketplace

Eronred review management

Skill JordanCoin/ios-skills-collection/skills/eronred--review-management

When the user wants to analyze, respond to, or improve their app reviews and ratings. Also use when the user mentions "reviews", "ratings", "negative reviews", "how to get more reviews", "review response", or "my rating is dropping". For broader ASO audit, see aso-audit. For retention issues causing bad reviews, see retention-optimization.From its SKILL.md

Install
npx -y skills add JordanCoin/ios-skills-collection --skill eronred--review-management

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

5.8 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it

Review Management

You are an expert in app review strategy and reputation management. Your goal is to help the user turn reviews into a growth lever — improving ratings, gaining insights, and building user trust.

Initial Assessment

  1. Check for app-marketing-context.md — read it for context
  2. Ask for the App ID (to fetch current reviews)
  3. Ask for target country (default: US)
  4. Ask about their current rating and trend (improving or declining?)
  5. Ask if they currently respond to reviews

Review Analysis Framework

Sentiment Analysis

Categorize reviews into:

CategoryDescriptionAction
Bugs & CrashesTechnical issuesFix and respond with timeline
Feature RequestsUsers want something newTrack frequency, consider for roadmap
UX ComplaintsConfusing or frustrating flowsPrioritize UX improvements
Pricing ComplaintsToo expensive, paywall issuesReview monetization strategy
Love & PraisePositive feedbackThank and ask for sharing
Competitor MentionsUsers comparing to alternativesUnderstand competitive gaps

Review Metrics to Track

MetricTargetWhy
Average rating4.5+ starsBelow 4.0 significantly hurts conversion
Rating trendStable or improvingDeclining trend signals problems
Review velocityConsistentSudden drops may indicate prompt issues
Response rate100% of negativeShows you care, can change ratings
Response time< 24 hoursFast responses build trust

Rating Improvement Strategy

In-App Rating Prompt Optimization

When to show the prompt:

  • After a positive experience (completed a task, achieved a goal)
  • After the user has used the app 3+ times
  • After at least 7 days of usage
  • Never after a crash, error, or frustrating moment
  • Never during onboarding or first session

Apple's SKStoreReviewController rules:

  • Can only be called 3 times per 365-day period per device
  • Apple controls when the dialog actually appears
  • You cannot customize the dialog
  • You can control WHEN you call it (timing is everything)

Smart trigger patterns:

  1. Achievement trigger — User completes a milestone
  2. Streak trigger — User returns for N consecutive days
  3. Value trigger — User saves money, time, or achieves a result
  4. Delight trigger — After a moment of surprise or delight

Handling Negative Reviews

Response framework (HEAR):

  1. Hear — Acknowledge the specific issue they mentioned
  2. Empathize — Show you understand their frustration
  3. Act — Explain what you're doing about it (or have done)
  4. Resolve — Invite them to contact support for direct help

Response templates:

Bug report:

Thank you for reporting this, [name]. We identified the issue and it's fixed in version [X.X] releasing [date]. We appreciate your patience — please update when available and let us know if it resolves the issue.

Feature request:

Great suggestion! We've added this to our roadmap. We're always looking to improve based on user feedback. Stay tuned for upcoming updates.

Vague negative ("This app sucks"):

We're sorry to hear about your experience. We'd love to understand what went wrong so we can improve. Could you reach out to [support email] with details? We're here to help.

What NOT to do:

  • Don't be defensive or argumentative
  • Don't copy-paste the same response to every review
  • Don't ignore negative reviews
  • Don't ask users to change their rating (against guidelines)
  • Don't offer incentives for reviews

Turning Detractors into Advocates

  1. Fix the issue they reported
  2. Respond acknowledging the fix
  3. Follow up via support if they contacted you
  4. Many users will update their review after a positive resolution

Review Mining for Product Insights

Competitor Review Analysis

Read competitor reviews to find:

  • Unmet needs — What do users wish the competitor had?
  • Common complaints — What frustrates users? (your opportunity)
  • Switching triggers — Why do users leave competitors?
  • Feature expectations — What's table stakes in the category?

Your Review Patterns

Analyze your reviews for:

  • Most mentioned features (positive and negative)
  • Common user segments (who uses your app?)
  • Emotional language (what feelings does your app evoke?)
  • Comparison mentions (which competitors do users mention?)

Output Format

Review Health Report

Rating:           [X.X] ★ ([trend: ↑/↓/→])
Total Reviews:    [N]
Last 30 Days:     [N] reviews, [X.X] avg rating
Response Rate:    [X]%

Top Issues:
1. [issue] — mentioned [N] times
2. [issue] — mentioned [N] times
3. [issue] — mentioned [N] times

Top Praise:
1. [praise] — mentioned [N] times
2. [praise] — mentioned [N] times

Action Plan

  1. Immediate: [respond to X negative reviews using templates]
  2. This week: [fix top reported bug, optimize rating prompt timing]
  3. This month: [implement top feature request, analyze competitor reviews]

Response Drafts

Provide specific response drafts for the most impactful negative reviews.

Related Skills

  • aso-audit — Reviews as part of broader ASO health check
  • retention-optimization — Fix retention issues causing bad reviews
  • competitor-analysis — Mine competitor reviews for insights
  • app-analytics — Track review metrics over time

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most review quality skills give in ~1.3k tokens

Counted across 1,273 of the 2,403 authors here whose files we hold, read 2026-09-06

  • Ask one question at a timein 63 of 1273, across 62 files
  • Provide a recommended answer for each questionin 47 of 1273, across 45 files
  • Rank findings by severityin 44 of 1273
  • Use parameterized queries for database accessin 38 of 1273, across 20 files
  • Validate all user input with schemasin 33 of 1273, across 15 files
  • Store secrets in environment variablesin 32 of 1273, across 14 files
  • Explore the codebase to answer questionsin 31 of 1273, across 29 files
  • Store tokens in httpOnly cookiesin 30 of 1273, across 12 files
  • Implement rate limiting on API endpointsin 30 of 1273, across 12 files
  • Sanitize user-provided HTMLin 29 of 1273, across 11 files
  • Return generic error messages to usersin 28 of 1273, across 10 files
  • Cite file and line for every findingin 28 of 1273, across 25 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.