app-store-optimization
Skill295 starsChanged 4 months agoMITView on GitHub
Use this skill when optimizing app store listings, researching keywords, or tracking mobile app performance on Apple App Store and Google Play Store.
12 other projects use a version of this, 5 of them edited.
Adopted by
Most recently taken up by
- darkweb19/skillsedited, first seen Nov 8, 2026
- kitloomlk-stack/mobile-apps-kittheir own version, first seen Oct 15, 2026
- xfstudio/skillstheir own version, first seen Oct 13, 2026
- Tgoldi/claude-skillsedited, first seen Oct 13, 2026
- thienqo/ios-skillstheir own version, first seen Oct 11, 2026
- Hassaan146/claude-skillsedited, first seen Jul 25, 2026
Used with
Projects with it also use ceo-advisor, senior-data-engineer and 2 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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Also in 3 projects that use this
Other versions12 projects use a version of this.
Word for word · 0
None found.
Edited · 5
- Hassaan146/claude-skills★ 1885% same
- Hussain-Elfalah/Agentic-Skills★ 278% same
- mahiunfiltered/claude-code-skills★ 185% same
- darkweb19/skills★ 085% same
- Tgoldi/claude-skills★ 095% same
Wrote their own version · 7
- alirezarezvani/claude-code-aso-skill★ 430same name
- kumaran-is/claude-code-onboarding★ 35same name
- xfstudio/skills★ 9same name
- thienqo/ios-skills★ 4same name
- ai4brands-design/claude-skills★ 2same name
- ffsshhttiikk/opencode-agents-skills★ 2same name
- kitloomlk-stack/mobile-apps-kit★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
- AGENTS.mdAGENTS.md
- android-keystore-generationSkill
- android-playstore-scanSkill
- android-playstore-setupSkill
- android-service-account-guideSkill
- readiness-checkSkill
The file
We split this skill into the rules it gives an agent
12 rules. 0 are common, 12 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 11 edited versions we read keep these.
12
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 53
Search volume (estimated monthly searches)
- Distinctive: line 61
Document keyword strategy for tracking
- Distinctive: line 102
Write subtitle (iOS) or short description (Android):
- Distinctive: line 107
Remove duplicates from title
- Distinctive: line 108
Remove plurals (Apple indexes both forms)
- Distinctive: line 109
No spaces after commas
- Distinctive: line 118
Validation: All fields within character limits.
- Distinctive: line 225
Verify compliance with guidelines
- Distinctive: line 232
Verify app is live in both stores
- Distinctive: line 238
Document any issues for quick fixes
- Distinctive: line 272
Test metadata and visual elements to improve conversion rates.
- Distinctive: line 296
Run test for minimum duration:
“Common” is measured: kept by at least 6 in 10 of the 11 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
App Store Optimization (ASO)
Workspace Context
Read bootstrap context before asking questions: strategy/brand.md for brand, audience, offer, channels, tools, constraints, and metrics; about/me.md for personal voice; content/ideas.md and content/calendar.md for content planning. Use legacy product-marketing context files only as fallback. Save generated drafts to content/<platform>/drafts/YYYY-MM-DD_short-topic-slug.md, and route durable learnings back to strategy/brand.md, about/me.md, or content/ideas.md.
Operating Contract
This skill is self-contained for its frontmatter scope: use its local instructions, references, scripts, and assets as the playbook; ask only for missing task-specific inputs; hand off to adjacent skills instead of expanding scope; and return an actionable artifact, decision, plan, draft, or diagnostic.
ASO tools for researching keywords, optimizing metadata, analyzing competitors, and improving app store visibility on Apple App Store and Google Play Store.
Keyword Research Workflow
Discover and evaluate keywords that drive app store visibility.
Workflow: Conduct Keyword Research
- Define target audience and core app functions:
- Primary use case (what problem does the app solve)
- Target user demographics
- Competitive category
- Generate seed keywords from:
- App features and benefits
- User language (not developer terminology)
- App store autocomplete suggestions
- Expand keyword list using:
- Modifiers (free, best, simple)
- Actions (create, track, organize)
- Audiences (for students, for teams, for business)
- Evaluate each keyword:
- Search volume (estimated monthly searches)
- Competition (number and quality of ranking apps)
- Relevance (alignment with app function)
- Score and prioritize keywords:
- Primary: Title and keyword field (iOS)
- Secondary: Subtitle and short description
- Tertiary: Full description only
- Map keywords to metadata locations
- Document keyword strategy for tracking
- Validation: Keywords scored; placement mapped; no competitor brand names included; no plurals in iOS keyword field
Keyword Evaluation Criteria
| Factor | Weight | High Score Indicators |
| Relevance | 35% | Describes core app function |
| Volume | 25% | 10,000+ monthly searches |
| Competition | 25% | Top 10 apps have <4.5 avg rating |
| Conversion | 15% | Transactional intent ("best X app") |
Keyword Placement Priority
| Location | Search Weight | Character Limit |
| App Title | Highest | 30 (iOS) / 50 (Android) |
| Subtitle (iOS) | High | 30 |
| Keyword Field (iOS) | High | 100 |
| Short Description (Android) | High | 80 |
| Full Description | Medium | 4,000 |
See: references/keyword-research-guide.md
Metadata Optimization Workflow
Optimize app store listing elements for search ranking and conversion.
Workflow: Optimize App Metadata
- Audit current metadata against platform limits:
- Title character count and keyword presence
- Subtitle/short description usage
- Keyword field efficiency (iOS)
- Description keyword density
- Optimize title following formula:
[Brand Name] - [Primary Keyword] [Secondary Keyword] - Write subtitle (iOS) or short description (Android):
- Focus on primary benefit
- Include secondary keyword
- Use action verbs
- Optimize keyword field (iOS only):
- Remove duplicates from title
- Remove plurals (Apple indexes both forms)
- No spaces after commas
- Prioritize by score
- Rewrite full description:
- Hook paragraph with value proposition
- Feature bullets with keywords
- Social proof section
- Call to action
- Validate character counts for each field
- Calculate keyword density (target 2-3% primary)
- Validation: All fields within character limits; primary keyword in title; no keyword stuffing (>5%); natural language preserved
Platform Character Limits
| Field | Apple App Store | Google Play Store |
| Title | 30 characters | 50 characters |
| Subtitle | 30 characters | N/A |
| Short Description | N/A | 80 characters |
| Keywords | 100 characters | N/A |
| Promotional Text | 170 characters | N/A |
| Full Description | 4,000 characters | 4,000 characters |
| What's New | 4,000 characters | 500 characters |
Description Structure
PARAGRAPH 1: Hook (50-100 words)
├── Address user pain point
├── State main value proposition
└── Include primary keyword
PARAGRAPH 2-3: Features (100-150 words)
├── Top 5 features with benefits
├── Bullet points for scanability
└── Secondary keywords naturally integrated
PARAGRAPH 4: Social Proof (50-75 words)
├── Download count or rating
├── Press mentions or awards
└── Summary of user testimonials
PARAGRAPH 5: Call to Action (25-50 words)
├── Clear next step
└── Reassurance (free trial, no signup)See: references/platform-requirements.md
Competitor Analysis Workflow
Analyze top competitors to identify keyword gaps and positioning opportunities.
Workflow: Analyze Competitor ASO Strategy
- Identify top 10 competitors:
- Direct competitors (same core function)
- Indirect competitors (overlapping audience)
- Category leaders (top downloads)
- Extract competitor keywords from:
- App titles and subtitles
- First 100 words of descriptions
- Visible metadata patterns
- Build competitor keyword matrix:
- Map which keywords each competitor targets
- Calculate coverage percentage per keyword
- Identify keyword gaps:
- Keywords with <40% competitor coverage
- High volume terms competitors miss
- Long-tail opportunities
- Analyze competitor visual assets:
- Icon design patterns
- Screenshot messaging and style
- Video presence and quality
- Compare ratings and review patterns:
- Average rating by competitor
- Common praise themes
- Common complaint themes
- Document positioning opportunities
- Validation: 10+ competitors analyzed; keyword matrix complete; gaps identified with volume estimates; visual audit documented
Competitor Analysis Matrix
| Analysis Area | Data Points |
| Keywords | Title keywords, description frequency |
| Metadata | Character utilization, keyword density |
| Visuals | Icon style, screenshot count/style |
| Ratings | Average rating, total count, velocity |
| Reviews | Top praise, top complaints |
Gap Analysis Template
| Opportunity Type | Example | Action |
| Keyword gap | "habit tracker" (40% coverage) | Add to keyword field |
| Feature gap | Competitor lacks widget | Highlight in screenshots |
| Visual gap | No videos in top 5 | Create app preview |
| Messaging gap | None mention "free" | Test free positioning |
App Launch Workflow
Execute a structured launch for maximum initial visibility.
Workflow: Launch App to Stores
- Complete pre-launch preparation (4 weeks before):
- Finalize keywords and metadata
- Prepare all visual assets
- Set up analytics (Firebase, Mixpanel)
- Build press kit and media list
- Submit for review (2 weeks before):
- Complete all store requirements
- Verify compliance with guidelines
- Prepare launch communications
- Configure post-launch systems:
- Set up review monitoring
- Prepare response templates
- Configure rating prompt timing
- Execute launch day:
- Verify app is live in both stores
- Announce across all channels
- Begin review response cycle
- Monitor initial performance (days 1-7):
- Track download velocity hourly
- Monitor reviews and respond within 24 hours
- Document any issues for quick fixes
- Conduct 7-day retrospective:
- Compare performance to projections
- Identify quick optimization wins
- Plan first metadata update
- Schedule first update (2 weeks post-launch)
- Validation: App live in stores; analytics tracking; review responses within 24h; download velocity documented; first update scheduled
Pre-Launch Checklist
| Category | Items |
| Metadata | Title, subtitle, description, keywords |
| Visual Assets | Icon, screenshots (all sizes), video |
| Compliance | Age rating, privacy policy, content rights |
| Technical | App binary, signing certificates |
| Analytics | SDK integration, event tracking |
| Marketing | Press kit, social content, email ready |
Launch Timing Considerations
| Factor | Recommendation |
| Day of week | Tuesday-Wednesday (avoid weekends) |
| Time of day | Morning in target market timezone |
| Seasonal | Align with relevant category seasons |
| Competition | Avoid major competitor launch dates |
See: references/aso-best-practices.md
A/B Testing Workflow
Test metadata and visual elements to improve conversion rates.
Workflow: Run A/B Test
- Select test element (prioritize by impact):
- Icon (highest impact)
- Screenshot 1 (high impact)
- Title (high impact)
- Short description (medium impact)
- Form hypothesis:
If we [change], then [metric] will [improve/increase] by [amount] because [rationale]. - Create variants:
- Control: Current version
- Treatment: Single variable change
- Calculate required sample size:
- Baseline conversion rate
- Minimum detectable effect (usually 5%)
- Statistical significance (95%)
- Launch test:
- Apple: Use Product Page Optimization
- Android: Use Store Listing Experiments
- Run test for minimum duration:
- At least 7 days
- Until statistical significance reached
- Analyze results:
- Compare conversion rates
- Check statistical significance
- Document learnings
- Validation: Single variable tested; sample size sufficient; significance reached (95%); results documented; winner implemented
A/B Test Prioritization
| Element | Conversion Impact | Test Complexity |
| App Icon | 10-25% lift possible | Medium (design needed) |
| Screenshot 1 | 15-35% lift possible | Medium |
| Title | 5-15% lift possible | Low |
| Short Description | 5-10% lift possible | Low |
| Video | 10-20% lift possible | High |
Sample Size Quick Reference
| Baseline CVR | Impressions Needed (per variant) |
| 1% | 31,000 |
| 2% | 15,500 |
| 5% | 6,200 |
| 10% | 3,100 |
Test Documentation Template
TEST ID: ASO-2025-001
ELEMENT: App Icon
HYPOTHESIS: A bolder color icon will increase conversion by 10%
START DATE: [Date]
END DATE: [Date]
RESULTS:
├── Control CVR: 4.2%
├── Treatment CVR: 4.8%
├── Lift: +14.3%
├── Significance: 97%
└── Decision: Implement treatment
LEARNINGS:
- Bold colors outperform muted tones in this category
- Apply to screenshot backgrounds for next testBefore/After Examples
Title Optimization
Productivity App:
| Version | Title | Analysis |
| Before | "MyTasks" | No keywords, brand only (8 chars) |
| After | "MyTasks - Todo List & Planner" | Primary + secondary keywords (29 chars) |
Fitness App:
| Version | Title | Analysis |
| Before | "FitTrack Pro" | Generic modifier (12 chars) |
| After | "FitTrack: Workout Log & Gym" | Category keywords (27 chars) |
Subtitle Optimization (iOS)
| Version | Subtitle | Analysis |
| Before | "Get Things Done" | Vague, no keywords |
| After | "Daily Task Manager & Planner" | Two keywords, benefit clear |
Keyword Field Optimization (iOS)
Before (Inefficient - 89 chars, 8 keywords):
task manager, todo list, productivity app, daily planner, reminder appAfter (Optimized - 97 chars, 14 keywords):
task,todo,checklist,reminder,organize,daily,planner,schedule,deadline,goals,habit,widget,sync,teamImprovements:
- Removed spaces after commas (+8 chars)
- Removed duplicates (task manager → task)
- Removed plurals (reminders → reminder)
- Removed words in title
- Added more relevant keywords
Description Opening
Before:
MyTasks is a comprehensive task management solution designed
to help busy professionals organize their daily activities
and boost productivity.After:
Forget missed deadlines. MyTasks keeps every task, reminder,
and project in one place—so you focus on doing, not remembering.
Trusted by 500,000+ professionals.Improvements:
- Leads with user pain point
- Specific benefit (not generic "boost productivity")
- Social proof included
- Keywords natural, not stuffed
Screenshot Caption Evolution
| Version | Caption | Issue |
| Before | "Task List Feature" | Feature-focused, passive |
| Better | "Create Task Lists" | Action verb, but still feature |
| Best | "Never Miss a Deadline" | Benefit-focused, emotional |
Tools and References
Scripts
| Script | Purpose | Usage |
| keyword_analyzer.py | Analyze keywords for volume and competition | python keyword_analyzer.py --keywords "todo,task,planner" |
| metadata_optimizer.py | Validate metadata character limits and density | python metadata_optimizer.py --platform ios --title "App Title" |
| competitor_analyzer.py | Extract and compare competitor keywords | python competitor_analyzer.py --competitors "App1,App2,App3" |
| aso_scorer.py | Calculate overall ASO health score | python aso_scorer.py --app-id com.example.app |
| ab_test_planner.py | Plan tests and calculate sample sizes | python ab_test_planner.py --cvr 0.05 --lift 0.10 |
| review_analyzer.py | Analyze review sentiment and themes | python review_analyzer.py --app-id com.example.app |
| launch_checklist.py | Generate platform-specific launch checklists | python launch_checklist.py --platform ios |
| localization_helper.py | Manage multi-language metadata | python localization_helper.py --locales "en,es,de,ja" |
References
| Document | Content |
| platform-requirements.md | iOS and Android metadata specs, visual asset requirements |
| aso-best-practices.md | Optimization strategies, rating management, launch tactics |
| keyword-research-guide.md | Research methodology, evaluation framework, tracking |
Assets
| Template | Purpose |
| aso-audit-template.md | Structured audit checklist for app store listings |
Platform Limitations
Data Constraints
| Constraint | Impact |
| No official keyword volume data | Estimates based on third-party tools |
| Competitor data limited to public info | Cannot see internal metrics |
| Review access limited to public reviews | No access to private feedback |
| Historical data unavailable for new apps | Cannot compare to past performance |
Platform Behavior
| Platform | Behavior |
| iOS | Keyword changes require app submission |
| iOS | Promotional text editable without update |
| Android | Metadata changes index in 1-2 hours |
| Android | No separate keyword field (use description) |
| Both | Algorithm changes without notice |
When Not to Use This Skill
| Scenario | Alternative |
| Web apps | Use web SEO skills |
| Enterprise apps (not public) | Internal distribution tools |
| Beta/TestFlight only | Focus on feedback, not ASO |
| Paid advertising strategy | Use paid acquisition skills |
Related Skills
| Skill | Integration Point |
| copywriting-core | App description copywriting |
| lead-generation-and-demand | Launch promotion campaigns |
| go-to-market-strategy | Go-to-market planning |
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