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review-management

When the user wants to analyze, respond to, or improve their app reviews and ratings.

Skill by appeeky

IndexedMIT★ 2,212
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/appeeky-review-management

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

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.

Use cases: security

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What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/review-management

What's inside

Skill name
review-management
Description
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.
License
MIT
Metadata
version: 1.0.0
Instructions
149 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# 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:

| Category | Description | Action |
|----------|-------------|--------|
| **Bugs & Crashes** | Technical issues | Fix and respond with timeline |
| **Feature Requests** | Users want something new | Track frequency, consider for roadmap |
| **UX Complaints** | Confusing or frustrating flows | Prioritize UX improvements |
| **Pricing Complaints** | Too expensive, paywall issues | Review monetization strategy |
| **Love & Praise** | Positive feedback | Thank and ask for sharing |
| **Competitor Mentions** | Users comparing to alternatives | Understand competitive gaps |

### Review Metrics to Track

| Metric | Target | Why |
|--------|--------|-----|
| Average rating | 4.5+ stars | Below 4.0 significantly hurts conversion |
| Rating trend | Stable or improving | Declining trend signals problems |
| Review velocity | Consistent | Sudden drops may indicate prompt issues |
| Response rate | 100% of negative | Shows you care, can change ratings |
| Response time | < 24 hours | Fast 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. **H**ear — Acknowledge the specific issue they mentioned
2. **E**mpathize — Show you understand their frustration
3. **A**ct — Explain what you're doing about it (or have done)
4. **R**esolve — 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

From appeeky/aso-skills, MIT.

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Forks
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Last commit (this folder)
Feb 27, 2026 (8 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
1.0.0
License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

Same skill elsewhere

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Cite this page

review-management skill. Agent Mart. https://agentmart.dev/skills/appeeky-review-management (last updated 2026-10-24)