| name | aso-reviews |
| description | Review and rating analysis for app store listings. Sentiment classification, keyword extraction from reviews, theme clustering, rating distribution, developer response strategy. Triggers on: "reviews", "ratings", "sentiment", "review response".
|
| user-invokable | true |
| argument-hint | <app-id> [--count 50] |
ASO Reviews — Review & Rating Management
Capabilities
- Rating distribution and trend analysis
- Sentiment classification (positive/neutral/negative)
- Theme clustering (performance, UI, features, pricing, bugs, support)
- Keyword extraction from review text (Android: reviews are indexed!)
- Developer response strategy and templates
- Review velocity assessment
Process
- Fetch reviews (from listing data or user-provided JSON)
- Run sentiment analysis:
uv run python scripts/review_analyzer.py --file reviews.json --json
- Extract keyword themes
- Analyze rating distribution
- Generate response templates for negative reviews
Scoring (0-100)
| Factor | Weight | Thresholds |
|---|
| Average rating | 30% | <3.5=Critical, 3.5-3.9=Poor, 4.0-4.4=Good, 4.5+=Excellent |
| Rating volume | 20% | <100=Low credibility, 100-1000=Moderate, >1000=Strong |
| Sentiment ratio | 20% | >70% positive=Good, 50-70%=Fair, <50%=Poor |
| Rating velocity | 15% | Improving trend=bonus, declining=penalty |
| Response rate | 15% | >80%=Excellent, 50-80%=Good, <50%=Needs work |
Platform-Specific Impact
iOS
- Reviews affect ranking via rating signals only
- Review TEXT is NOT indexed for search
- Developer responses shown prominently — build trust
- Rating resets possible with major version updates
Android
- Review TEXT IS INDEXED — keywords in reviews impact search visibility
- Keywords from reviews can boost rankings for mentioned features
- Encourage reviews that mention key use cases
- No rating reset option
Response Strategy: HEAR Framework
- Hear — Acknowledge the specific concern
- Empathize — Show understanding
- Act — Describe what you're doing about it
- Resolve — Provide next steps or solution
Response Templates
1-2 star (bug/crash):
Thank you for reporting this. We've identified the [specific issue] and our team is working on a fix for the next update. Please contact us at [email] if you need immediate help.
1-2 star (feature request):
We appreciate your feedback about [feature]. This is on our roadmap and we're actively working on it. We'll keep you updated.
3 star (mixed):
Thanks for the detailed feedback! We're glad [positive aspect] is working well. We hear you on [negative aspect] and are improving it in upcoming updates.
4-5 star:
Thank you for the kind words! We're thrilled you enjoy [specific feature]. Your support means a lot to our team.
Output Format
# Review Analysis: [App Name]
## Rating Health
- Average: X.X/5.0
- Distribution: [histogram]
- Volume: X total reviews
- Velocity: X reviews/week
## Sentiment Analysis
- Positive: X%
- Neutral: X%
- Negative: X%
## Top Themes
| Theme | Mentions | Sentiment | Key Quotes |
|-------|----------|-----------|------------|
## Keyword Opportunities (from reviews)
[Keywords frequently mentioned that could inform metadata]
## Recommended Response Actions
[Prioritized list of reviews to respond to]
Available Tools
Read, Bash, Write, Glob, Grep
