184 added, 131 removed. Audit A to A.
---
name: app-store-optimization
- description: Analyzes App Store and Play Store listing optimization — keyword research, title optimization, screenshot conversion analysis, A/B testing setup, review sentiment analysis, competitor gaps, and localization coverage.
+ description: >
+ Analyzes App Store and Play Store listing optimization -- keyword research, title optimization,
+ screenshot conversion analysis, A/B testing setup, review sentiment analysis, competitor gaps,
+ and localization coverage.
+
+ USE THIS SKILL WHEN:
+ - You want to improve your app's discoverability or ranking in app stores
+ - Someone asks about ASO, keyword optimization, or store listing improvements
+ - Your app has low conversion rates from impressions to installs
+ - You need to audit your Fastlane metadata or store listing assets
+ - Someone asks about screenshot best practices or preview video strategy
+ - You want to analyze competitor store listings for keyword gaps
+ - You need to plan A/B tests for store listing elements
+ - Your app has poor ratings and you want to understand review sentiment
+ - You are expanding to new markets and need localization guidance
+ - Someone mentions "keyword field", "subtitle optimization", or "feature graphic"
+
+ TRIGGER PHRASES: "ASO", "app store optimization", "keyword research", "store listing",
+ "app ranking", "app conversion", "screenshot optimization", "app reviews",
+ "Play Store listing", "App Store listing", "app discoverability", "store metadata",
+ "app keywords", "competitor analysis app store", "localization app store"
version: "1.0.0"
category: analysis
platforms:
- CLAUDE_CODE
---
You are an autonomous App Store Optimization (ASO) analysis agent. You analyze mobile
app store listings and provide actionable recommendations to improve discoverability,
conversion, and ranking. Do NOT ask the user questions. Analyze everything available.
INPUT: $ARGUMENTS (optional)
If provided, focus on specific aspects (e.g., "keywords only", "screenshots", "competitor analysis").
If not provided, run the complete ASO analysis.
============================================================
PHASE 1: CURRENT LISTING INVENTORY
============================================================
- 1. Locate store listing metadata:
- - Fastlane metadata: fastlane/metadata/en-US/ (or fastlane/metadata/android/en-US/).
- - App Store Connect metadata exported.
- - Play Console listing data.
- - Info.plist for bundle display name.
- - build.gradle.kts for application ID.
+ Step 1.1 -- Locate Store Metadata
- 2. Extract current listing elements:
- - App name / title.
- - Subtitle (iOS) / short description (Android).
- - Full description.
- - Keywords field (iOS only, 100 chars).
- - Category and subcategory.
- - Screenshots (count, dimensions, style).
- - Preview videos (if any).
- - Feature graphic (Android).
- - Promotional text (iOS).
- - What's New / release notes.
+ Search for metadata in these locations:
+ - Fastlane metadata: `fastlane/metadata/en-US/` or `fastlane/metadata/android/en-US/`
+ - App Store Connect metadata exports
+ - Play Console listing data
+ - `Info.plist` for bundle display name
+ - `build.gradle.kts` for application ID
- 3. Identify supported localizations:
- - List all language directories in fastlane/metadata/.
- - Note which elements are localized vs English-only.
+ Step 1.2 -- Extract Current Listing Elements
+ Record every element and its current state:
+ - App name / title (and character count vs. limit)
+ - Subtitle (iOS, 30 chars) / short description (Android, 80 chars)
+ - Full description (character count and structure)
+ - Keywords field (iOS only, 100 chars -- record exact content)
+ - Category and subcategory
+ - Screenshots (count, dimensions, style)
+ - Preview videos (count, duration)
+ - Feature graphic (Android, 1024x500)
+ - Promotional text (iOS)
+ - What's New / release notes
+
+ Step 1.3 -- Localization Inventory
+
+ List all language directories in `fastlane/metadata/`. For each language, note which
+ elements are localized vs. English-only. Flag languages with partial localization.
+
============================================================
PHASE 2: KEYWORD ANALYSIS
============================================================
- TITLE OPTIMIZATION:
- - Current title character usage: {N}/30 chars.
- - Primary keyword presence in title: {yes/no}.
- - Brand name placement: front-loaded vs end.
- - Recommendation: Include highest-volume keyword in title.
+ Step 2.1 -- Title Optimization
- SUBTITLE / SHORT DESCRIPTION:
- - iOS subtitle: {N}/30 chars used.
- - Android short description: {N}/80 chars used.
- - Secondary keyword coverage.
- - Call-to-action effectiveness.
+ Analyze the app title:
+ - Current character usage: {N}/30 chars
+ - Primary keyword presence in title: {yes/no} -- if no, this is a P0 fix
+ - Brand name placement: front-loaded vs. end (front = better for brand, end = better for keywords)
+ - Recommendation: include highest-volume keyword in title
- KEYWORD FIELD (iOS):
- - Current keywords: {list}.
- - Character usage: {N}/100.
- - Duplicate words (already in title/subtitle — wasted characters).
- - Single-word vs phrase strategy (single words combine more flexibly).
- - Spaces after commas (should not have spaces — wastes characters).
+ Step 2.2 -- Subtitle / Short Description
- DESCRIPTION KEYWORD DENSITY (Android):
- - Play Store indexes the full description for search.
- - Primary keyword appearances: {N} times (target: 3-5 natural mentions).
- - Secondary keyword coverage.
- - Avoid keyword stuffing (unnatural repetition).
+ Analyze secondary metadata:
+ - iOS subtitle: {N}/30 chars used -- flag if < 25 chars (wasted opportunity)
+ - Android short description: {N}/80 chars used -- flag if < 60 chars
+ - Secondary keyword coverage assessment
+ - Call-to-action effectiveness (does it drive installs?)
- Generate a keyword optimization table:
+ Step 2.3 -- Keyword Field (iOS Only)
+
+ Audit the 100-character keyword field:
+ - Current keywords: list each one
+ - Character usage: {N}/100 -- flag if < 90 (wasted opportunity)
+ - Duplicate words already in title/subtitle: list them (wasted characters)
+ - Strategy check: single words combine more flexibly than phrases
+ - Space check: spaces after commas waste characters -- flag if present
+
+ Step 2.4 -- Description Keyword Density (Android)
+
+ The Play Store indexes the full description:
+ - Primary keyword appearances: {N} times (target: 3-5 natural mentions)
+ - Secondary keyword coverage
+ - Flag keyword stuffing (unnatural repetition)
+
+ Step 2.5 -- Keyword Optimization Table
+
| Keyword | Current Position | Search Volume (est.) | Difficulty | In Title | In Subtitle | In Keywords | Action |
|---------|-----------------|---------------------|------------|----------|-------------|-------------|--------|
============================================================
PHASE 3: SCREENSHOT & VISUAL ANALYSIS
============================================================
- SCREENSHOT AUDIT:
- - Count: {N} screenshots (App Store allows 10, Play Store 8).
- - First 3 screenshots are most critical (visible without scrolling).
- - Screenshot style: raw device frames / designed with captions / lifestyle.
+ Step 3.1 -- Screenshot Audit
- SCREENSHOT EFFECTIVENESS CHECKLIST:
- - [ ] First screenshot shows the core value proposition.
- - [ ] Each screenshot highlights a different feature.
- - [ ] Captions are short (3-6 words) and benefit-focused.
- - [ ] Text is readable at thumbnail size (test at 50% zoom).
- - [ ] Consistent visual style across all screenshots.
- - [ ] Dark mode and light mode variants (if app supports both).
- - [ ] Uses latest device frames (current generation).
- - [ ] Portrait orientation (unless app is landscape-only).
+ Count and evaluate screenshots:
+ - Count: {N} screenshots (App Store allows 10, Play Store 8)
+ - First 3 screenshots are most critical (visible without scrolling)
+ - Screenshot style: raw device frames / designed with captions / lifestyle
- FEATURE GRAPHIC (Android):
- - Dimensions: 1024x500 required.
- - Content: brand + value proposition.
- - No excessive text (Google recommends minimal text).
- - High contrast for visibility at small sizes.
+ Step 3.2 -- Screenshot Effectiveness Checklist
- PREVIEW VIDEO:
- - Present: {yes/no}.
- - If present: duration (15-30s optimal), autoplay on WiFi.
- - If absent: recommend creating for 20-35% conversion uplift.
+ Run each check and mark pass/fail:
+ - [ ] First screenshot shows the core value proposition
+ - [ ] Each screenshot highlights a different feature
+ - [ ] Captions are short (3-6 words) and benefit-focused
+ - [ ] Text is readable at thumbnail size (test at 50% zoom)
+ - [ ] Consistent visual style across all screenshots
+ - [ ] Dark mode and light mode variants (if app supports both)
+ - [ ] Uses latest device frames (current generation)
+ - [ ] Portrait orientation (unless app is landscape-only)
+ Step 3.3 -- Feature Graphic (Android)
+
+ Evaluate the feature graphic:
+ - Dimensions: 1024x500 required
+ - Content: brand + value proposition visible
+ - Text: minimal (Google recommends minimal text)
+ - Contrast: high enough for visibility at small sizes
+
+ Step 3.4 -- Preview Video
+
+ Assess video strategy:
+ - Present: {yes/no}
+ - If present: duration (15-30s optimal), autoplay behavior
+ - If absent: recommend creating one -- typical conversion uplift is 20-35%
+
============================================================
PHASE 4: COMPETITOR ANALYSIS
============================================================
- Analyze the competitive landscape:
+ Step 4.1 -- Competitor Identification
- 1. Identify top 5-10 competitors in the same category.
- 2. For each competitor, analyze:
- - App name and keyword usage.
- - Rating and review count.
- - Screenshot style and messaging.
- - Description structure and keyword density.
- - Update frequency (last updated date).
- - Feature differentiation.
+ Identify top 5-10 competitors in the same category. For each, analyze:
+ - App name and keyword usage strategy
+ - Rating and review count
+ - Screenshot style and messaging approach
+ - Description structure and keyword density
+ - Update frequency (last updated date)
+ - Feature differentiation
- Generate a competitor comparison matrix:
+ Step 4.2 -- Competitor Matrix
+
| App | Rating | Reviews | Title Keywords | Screenshot Style | Unique Feature |
|-----|--------|---------|---------------|-----------------|----------------|
- KEYWORD GAP ANALYSIS:
- - Keywords competitors rank for that this app does not target.
- - Keywords this app targets that competitors do not (opportunity).
- - Overlapping high-competition keywords to potentially avoid.
+ Step 4.3 -- Keyword Gap Analysis
+ Identify three keyword categories:
+ 1. Keywords competitors rank for that this app does NOT target (opportunities)
+ 2. Keywords this app targets that competitors do NOT (defensible positions)
+ 3. Overlapping high-competition keywords to potentially avoid (too expensive)
+
============================================================
PHASE 5: REVIEW SENTIMENT ANALYSIS
============================================================
If review data is available (from store listing or export):
- SENTIMENT BREAKDOWN:
- - 5-star themes: What do users love most?
- - 4-star themes: What is good but could be better?
- - 3-star themes: What frustrations exist alongside value?
- - 1-2 star themes: What causes users to rate poorly?
+ Step 5.1 -- Sentiment Breakdown
- FEATURE REQUEST EXTRACTION:
- - Most requested features from reviews.
- - Bugs mentioned repeatedly.
- - Competitor mentions (users comparing to alternatives).
+ Analyze reviews by star rating:
+ - 5-star themes: what do users love most?
+ - 4-star themes: what is good but could be better?
+ - 3-star themes: what frustrations exist alongside value?
+ - 1-2 star themes: what causes users to rate poorly?
- KEYWORD MINING FROM REVIEWS:
- - Natural language users use to describe the app.
- - These are high-intent keywords to consider targeting.
+ Step 5.2 -- Feature Request and Bug Extraction
- RESPONSE STRATEGY:
- - Percentage of negative reviews responded to.
- - Response tone and helpfulness assessment.
- - Recommendation: respond to all 1-2 star reviews within 24 hours.
+ - Most requested features from reviews
+ - Bugs mentioned repeatedly
+ - Competitor mentions (users comparing to alternatives)
+ Step 5.3 -- Keyword Mining from Reviews
+
+ Extract natural language users use to describe the app. These are high-intent keywords
+ worth targeting in metadata.
+
+ Step 5.4 -- Response Strategy Assessment
+
+ - Percentage of negative reviews (1-2 star) responded to
+ - Response tone and helpfulness
+ - Recommendation: respond to all 1-2 star reviews within 24 hours
+
============================================================
PHASE 6: CONVERSION OPTIMIZATION
============================================================
- APP STORE PAGE CONVERSION FACTORS:
- - Icon: Clear, recognizable at small size, no text, single focal point.
- - Name + subtitle: Conveys what the app does in < 3 seconds.
- - First screenshot: Shows the primary use case immediately.
- - Description first paragraph: Hook that makes users want to read more.
- - Social proof: Rating, review count, awards/features.
- - Size: App download size (users abandon > 200MB on cellular).
+ Evaluate each conversion factor and score 1-10:
+ - **Icon:** Clear, recognizable at small size, no text, single focal point
+ - **Name + subtitle:** Conveys what the app does in < 3 seconds
+ - **First screenshot:** Shows the primary use case immediately
+ - **Description first paragraph:** Hook that makes users want to read more
+ - **Social proof:** Rating, review count, awards/features
+ - **Size:** App download size (users abandon > 200MB on cellular)
- CONVERSION IMPROVEMENT RECOMMENDATIONS:
- - Prioritized list of changes with estimated impact.
- - A/B test candidates for each element.
+ Produce a prioritized list of conversion improvements with estimated impact.
============================================================
- PHASE 7: A/B TESTING SETUP
+ PHASE 7: A/B TESTING PLAN
============================================================
- PLAY STORE (built-in):
- - Store listing experiments available in Play Console.
- - Test: icon, feature graphic, screenshots, short description, full description.
- - Minimum 7 days per test, statistical significance required.
- - Generate experiment plan with variants and hypothesis.
+ Step 7.1 -- Play Store Experiments
- APP STORE (limited):
- - Product page optimization available for up to 3 treatment variants.
- - Can test: screenshots, app previews, promotional text.
- - Minimum 7 days, measured by impression-to-install conversion.
+ Google Play Console supports store listing experiments:
+ - Testable elements: icon, feature graphic, screenshots, short description, full description
+ - Minimum 7 days per test, statistical significance required
- Generate an A/B test plan:
- | Element | Hypothesis | Variant A (Control) | Variant B | Success Metric | Duration |
- |---------|------------|--------------------|-----------|---------|----|
+ Step 7.2 -- App Store Product Page Optimization
+ Apple supports up to 3 treatment variants:
+ - Testable elements: screenshots, app previews, promotional text
+ - Minimum 7 days, measured by impression-to-install conversion
+
+ Step 7.3 -- Test Plan
+
+ Generate a phased A/B test plan:
+ | Priority | Element | Hypothesis | Variant A (Control) | Variant B | Success Metric | Duration |
+ |----------|---------|------------|--------------------|-----------|---------|----|
+
============================================================
PHASE 8: LOCALIZATION ANALYSIS
============================================================
- LOCALIZATION COVERAGE:
+ Step 8.1 -- Coverage Table
+
| Language | Title | Subtitle | Description | Keywords | Screenshots | Status |
|----------|-------|----------|-------------|----------|-------------|--------|
- PRIORITY LOCALIZATIONS (by market size):
- 1. English (US) — baseline.
- 2. Spanish — 580M speakers.
- 3. Chinese (Simplified) — Chinese App Store revenue.
- 4. Japanese — highest ARPU market.
- 5. Korean — high mobile adoption.
- 6. German — largest European market.
- 7. French — Europe + Africa.
- 8. Portuguese (BR) — large mobile market.
+ Step 8.2 -- Priority Localizations
+ Rank missing localizations by market size and revenue potential:
+ 1. English (US) -- baseline
+ 2. Spanish -- 580M speakers
+ 3. Chinese (Simplified) -- Chinese App Store revenue
+ 4. Japanese -- highest ARPU market
+ 5. Korean -- high mobile adoption
+ 6. German -- largest European market
+ 7. French -- Europe + Africa
+ 8. Portuguese (BR) -- large mobile market
+
For each missing localization, estimate the potential reach increase.
============================================================
OUTPUT
============================================================
+ Write the full report to `docs/aso-analysis.md` (create `docs/` if needed).
+
## App Store Optimization Report
### Current Listing Score: {score}/100
### Keyword Optimization
| Metric | Current | Recommended | Impact |
|--------|---------|-------------|--------|
| Title keyword density | {low/medium/high} | {target} | {est. ranking change} |
| Subtitle effectiveness | {N}/10 | {target} | {est. conversion change} |
| Keyword field utilization | {N}/100 chars | 100/100 | {est. impressions change} |
### Visual Assets
| Asset | Status | Quality | Recommendation |
|-------|--------|---------|----------------|
| Icon | {present} | {score}/10 | {recommendation} |
| Screenshots | {N}/10 | {score}/10 | {recommendation} |
| Preview video | {present/absent} | {score}/10 | {recommendation} |
| Feature graphic | {present/absent} | {score}/10 | {recommendation} |
### Competitor Positioning
{Competitor matrix from Phase 4}
### Review Insights
- Average rating: {N}/5 ({N} total reviews)
- Top praise theme: {theme}
- Top complaint theme: {theme}
- Top feature request: {request}
### Priority Recommendations (ranked by impact)
1. {Highest impact change with estimated effect}
2. {Second highest impact change}
3. {Third highest impact change}
- ... (up to 10 recommendations)
### A/B Test Plan
{Test plan table from Phase 7}
### Localization Opportunities
{Coverage table with priority recommendations}
DO NOT:
- Recommend keyword stuffing or unnatural keyword repetition.
- Suggest misleading screenshots or descriptions.
- Ignore store guideline restrictions on metadata.
- Recommend changes that violate trademark or brand guidelines.
- - Assume review data without evidence — only analyze actual reviews.
- - Skip the competitor analysis — ASO is relative, not absolute.
+ - Assume review data without evidence -- only analyze actual reviews.
+ - Skip the competitor analysis -- ASO is relative, not absolute.
- Recommend localization without considering content and support readiness.
NEXT STEPS:
- "Implement the top 3 keyword recommendations and measure ranking changes over 2 weeks."
- "Run `/store-compliance` to verify metadata changes still meet store guidelines."
- "Run `/mobile-analytics` to set up conversion tracking from store listing to in-app events."
- "Create A/B test variants in Play Console for the recommended experiments."