App Store Optimization

App Store Optimization (ASO)

ASO tools for researching keywords, optimizing metadata, analyzing competitors, and improving app store visibility on Apple App Store and Google Play Store. This file is a lean map — execute a task by loading the matching reference below.

Core Capabilities

• Keyword research — seed/expand/score keywords by relevance, volume, competition, and conversion intent; map to metadata placements
• Metadata optimization — title, subtitle/short description, iOS keyword field, and full description against platform character limits and density targets
• Competitor analysis — keyword matrices, gap analysis, visual and ratings benchmarking across the top 10 competitors
• Launch & A/B testing — structured launch checklists, timing, and conversion experiments with sample-size and significance math
• Reviews & localization — sentiment/theme/issue extraction and multi-market metadata adaptation
• 8 Python tools — keyword_analyzer, metadata_optimizer, competitor_analyzer, aso_scorer, ab_test_planner, review_analyzer, launch_checklist, localization_helper (stdlib only, analyze data you provide)

When to Use

• Researching or scoring keywords for an app store listing
• Optimizing a title/subtitle/description/keyword field for ranking and conversion
• Auditing competitors for keyword gaps and positioning opportunities
• Planning an app launch or running a store-listing A/B test
• Analyzing reviews or planning multi-market localization

Clarify First

Before generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• [ ] Platform — Apple App Store vs Google Play (different character limits, keyword field vs description indexing, ranking factors)
• [ ] App category + seed keywords — the app's space and starting terms (drives keyword research + scoring)
• [ ] Primary goal — ranking visibility vs conversion rate (shapes metadata, title/subtitle, and screenshot priorities)
• [ ] Target market/locale — which storefronts (drives localization + keyword volume estimates)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

python scripts/keyword_analyzer.py --keywords "todo,task,planner"
python scripts/metadata_optimizer.py --platform ios --title "App Title"
python scripts/aso_scorer.py --app-id com.example.app

Note: the scripts are importable Python libraries — see the Tool Reference for classes, methods, and convenience functions.

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

• [references/aso-workflows.md](references/aso-workflows.md) — step-by-step procedures, scoring criteria, placement tables, structure diagrams, templates, and before/after examples for all five workflows. Read when executing keyword research, metadata optimization, competitor analysis, launch, or A/B testing.
• [references/tool-reference.md](references/tool-reference.md) — full usage for the 8 Python scripts: classes, methods, parameters, returns, convenience functions, plus the scripts and assets tables. Read before invoking a tool.
• [references/operations-and-benchmarks.md](references/operations-and-benchmarks.md) — troubleshooting table, success criteria/targets, platform limitations, proactive triggers, output artifacts, communication standards, related skills, and the full integration matrix. Read when diagnosing issues, setting targets, or wiring into other tools.
• [references/keyword-research-guide.md](references/keyword-research-guide.md) — research methodology, evaluation framework, and tracking. Read for deep keyword discovery and selection.
• [references/platform-requirements.md](references/platform-requirements.md) — iOS and Android metadata specs and visual asset requirements. Read when validating fields against platform rules.
• [references/aso-best-practices.md](references/aso-best-practices.md) — optimization strategies, rating management, and launch tactics. Read for proven tactics and playbooks.

Scope & Limitations

In scope: keyword research, metadata optimization and character-limit validation, competitor ASO analysis (public data), A/B test planning with significance math, launch/seasonal/localization planning, and review sentiment analysis for Apple App Store and Google Play Store.

Out of scope: real-time store data fetching (scripts analyze static data you provide), Apple Search Ads / Google Ads campaign management, creative asset design, cross-device attribution (use an MMP), in-app analytics/retention, and revenue/subscription pricing.

Data constraints: no official search-volume API exists for either store (estimates use third-party tools or heuristics); competitor and review data are limited to public info; historical ranking data needs external tools (AppTweak, Sensor Tower, data.ai); Apple's June 2025 update indexes screenshot text, which these scripts do not yet analyze. See references/operations-and-benchmarks.md for details.

Integration Points

Connects to Apple App Store Connect and Google Play Console (metadata submission, Product Page Optimization / Store Listing Experiments), Apple Search Ads (keyword discovery), ASO tools (AppTweak, Sensor Tower, data.ai for volume/ranking data), analytics (Firebase/Mixpanel/Amplitude for engagement signals), and the campaign-analytics and content-creator skills. Full connection details and data flows: references/operations-and-benchmarks.md.

ASO Audit Template

Use this template to conduct a systematic App Store Optimization audit.

---

App Information

---

Metadata Audit

Title Analysis

Title Score: ___/10

Recommendations:

• [ ]
• [ ]

Subtitle / Short Description

Score: ___/10

Recommendations:

• [ ]
• [ ]

Keyword Field (iOS Only)

Score: ___/10

Recommendations:

• [ ]
• [ ]

Full Description

Score: ___/10

Recommendations:

• [ ]
• [ ]

---

Visual Asset Audit

App Icon

Score: ___/10

Recommendations:

• [ ]
• [ ]

Screenshots

Overall Screenshot Score: ___/10

Recommendations:

• [ ]
• [ ]

App Preview Video

Score: ___/10

---

Keyword Performance Audit

Current Keyword Rankings

Keyword Opportunities

---

Rating & Review Audit

Rating Summary

Review Analysis

Response Rate

Rating Score: ___/10

Recommendations:

• [ ]
• [ ]

---

Competitor Comparison

Top 3 Competitors

Competitive Gaps

---

Overall ASO Score

---

Priority Action Items

High Priority (This Week)

1. [ ] 2. [ ] 3. [ ]

Medium Priority (This Month)

1. [ ] 2. [ ] 3. [ ]

Low Priority (This Quarter)

1. [ ] 2. [ ] 3. [ ]

---

Audit Sign-Off

---

Notes

_Additional observations and context:_

How to Use the App Store Optimization Skill

Hey Claude—I just added the "app-store-optimization" skill. Can you help me optimize my app's presence on the App Store and Google Play?

Example Invocations

Keyword Research

Example 1: Basic Keyword Research

Hey Claude—I just added the "app-store-optimization" skill. Can you research the best keywords for my productivity app? I'm targeting professionals who need task management and team collaboration features.

Example 2: Competitive Keyword Analysis

Hey Claude—I just added the "app-store-optimization" skill. Can you analyze keywords that Todoist, Asana, and Monday.com are using? I want to find gaps and opportunities for my project management app.

Metadata Optimization

Example 3: Optimize App Title

Hey Claude—I just added the "app-store-optimization" skill. Can you optimize my app title for the Apple App Store? My app is called "TaskFlow" and I want to rank for "task manager", "productivity", and "team collaboration". The title needs to be under 30 characters.

Example 4: Full Metadata Package

Hey Claude—I just added the "app-store-optimization" skill. Can you create optimized metadata for both Apple App Store and Google Play Store? Here's my app info:
- Name: TaskFlow
- Category: Productivity
- Key features: AI task prioritization, team collaboration, calendar integration
- Target keywords: task manager, productivity app, team tasks

Competitor Analysis

Example 5: Analyze Top Competitors

Hey Claude—I just added the "app-store-optimization" skill. Can you analyze the ASO strategies of the top 5 productivity apps in the App Store? I want to understand their title strategies, keyword usage, and visual asset approaches.

Example 6: Identify Competitive Gaps

Hey Claude—I just added the "app-store-optimization" skill. Can you compare my app's ASO performance against competitors and identify what I'm missing? Here's my current metadata: [paste metadata]

ASO Score Calculation

Example 7: Calculate Overall ASO Health

Hey Claude—I just added the "app-store-optimization" skill. Can you calculate my app's ASO health score? Here are my metrics:
- Average rating: 4.2 stars
- Total ratings: 3,500
- Keywords in top 10: 3
- Keywords in top 50: 12
- Conversion rate: 4.5%

Example 8: Identify Improvement Areas

Hey Claude—I just added the "app-store-optimization" skill. My ASO score is 62/100. Can you tell me which areas I should focus on first to improve my rankings and downloads?

A/B Testing

Example 9: Plan Icon Test

Hey Claude—I just added the "app-store-optimization" skill. I want to A/B test two different app icons. My current conversion rate is 5%. Can you help me plan the test, calculate required sample size, and determine how long to run it?

Example 10: Analyze Test Results

Hey Claude—I just added the "app-store-optimization" skill. Can you analyze my A/B test results?
- Variant A (control): 2,500 visitors, 125 installs
- Variant B (new icon): 2,500 visitors, 150 installs
Is this statistically significant? Should I implement variant B?

Localization

Example 11: Plan Localization Strategy

Hey Claude—I just added the "app-store-optimization" skill. I currently only have English metadata. Which markets should I localize for first? I'm a bootstrapped startup with moderate budget.

Example 12: Translate Metadata

Hey Claude—I just added the "app-store-optimization" skill. Can you help me translate my app metadata to Spanish for the Mexico market? Here's my English metadata: [paste metadata]. Check if it fits within character limits.

Review Analysis

Example 13: Analyze User Reviews

Hey Claude—I just added the "app-store-optimization" skill. Can you analyze my recent reviews and tell me:
- Overall sentiment (positive/negative ratio)
- Most common complaints
- Most requested features
- Bugs that need immediate fixing

Example 14: Generate Review Response Templates

Hey Claude—I just added the "app-store-optimization" skill. Can you create professional response templates for:
- Users reporting crashes
- Feature requests
- Positive 5-star reviews
- General complaints

Launch Planning

Example 15: Pre-Launch Checklist

Hey Claude—I just added the "app-store-optimization" skill. Can you generate a comprehensive pre-launch checklist for both Apple App Store and Google Play Store? My launch date is December 1, 2025.

Example 16: Optimize Launch Timing

Hey Claude—I just added the "app-store-optimization" skill. What's the best day and time to launch my fitness app? I want to maximize visibility and downloads in the first week.

Example 17: Plan Seasonal Campaign

Hey Claude—I just added the "app-store-optimization" skill. Can you identify seasonal opportunities for my fitness app? It's currently October—what campaigns should I run for the next 6 months?

What to Provide

For Keyword Research

• App name and category
• Target audience description
• Key features and unique value proposition
• Competitor apps (optional)
• Geographic markets to target

For Metadata Optimization

• Current app name
• Platform (Apple, Google, or both)
• Target keywords (prioritized list)
• Key features and benefits
• Target audience
• Current metadata (for optimization)

For Competitor Analysis

• Your app category
• List of competitor app names or IDs
• Platform (Apple or Google)
• Specific aspects to analyze (keywords, visuals, ratings)

For ASO Score Calculation

• Metadata quality metrics (title length, description length, keyword density)
• Rating data (average rating, total ratings, recent ratings)
• Keyword rankings (top 10, top 50, top 100 counts)
• Conversion metrics (impression-to-install rate, downloads)

For A/B Testing

• Test type (icon, screenshot, title, description)
• Control variant details
• Test variant details
• Baseline conversion rate
• For results analysis: visitor and conversion counts for both variants

For Localization

• Current market and language
• Budget level (low, medium, high)
• Target number of markets
• Current metadata text for translation

For Review Analysis

• Recent reviews (text, rating, date)
• Platform (Apple or Google)
• Time period to analyze
• Specific focus (bugs, features, sentiment)

For Launch Planning

• Platform (Apple, Google, or both)
• Target launch date
• App category
• App information (name, features, target audience)

What You'll Get

Keyword Research Output

• Prioritized keyword list with search volume estimates
• Competition level analysis
• Relevance scores
• Long-tail keyword opportunities
• Strategic recommendations

Metadata Optimization Output

• Optimized titles (multiple options)
• Optimized descriptions (short and full)
• Keyword field optimization (Apple)
• Character count validation
• Keyword density analysis
• Before/after comparison

Competitor Analysis Output

• Ranked competitors by ASO strength
• Common keyword patterns
• Keyword gaps and opportunities
• Visual asset assessment
• Best practices identified
• Actionable recommendations

ASO Score Output

• Overall score (0-100)
• Breakdown by category (metadata, ratings, keywords, conversion)
• Strengths and weaknesses
• Prioritized action items
• Expected impact of improvements

A/B Test Output

• Test design with hypothesis
• Required sample size calculation
• Duration estimates
• Statistical significance analysis
• Implementation recommendations
• Learnings and insights

Localization Output

• Prioritized target markets
• Estimated translation costs
• ROI projections
• Character limit validation for each language
• Cultural adaptation recommendations
• Phased implementation plan

Review Analysis Output

• Sentiment distribution (positive/neutral/negative)
• Common themes and topics
• Top issues requiring fixes
• Most requested features
• Response templates
• Trend analysis over time

Launch Planning Output

• Platform-specific checklists (Apple, Google, Universal)
• Timeline with milestones
• Compliance validation
• Optimal launch timing recommendations
• Seasonal campaign opportunities
• Update cadence planning

Tips for Best Results

1. Be Specific: Provide as much detail about your app as possible 2. Include Context: Share your goals (increase downloads, improve ranking, boost conversion) 3. Provide Data: Real metrics enable more accurate analysis 4. Iterate: Start with keyword research, then optimize metadata, then test 5. Track Results: Monitor changes after implementing recommendations 6. Stay Compliant: Always verify recommendations against current App Store/Play Store guidelines 7. Test First: Use A/B testing before making major metadata changes 8. Localize Strategically: Start with highest-ROI markets first 9. Respond to Reviews: Use provided templates to engage with users 10. Plan Ahead: Use launch checklists and timelines to avoid last-minute rushes

Common Workflows

New App Launch

1. Keyword research → Competitor analysis → Metadata optimization → Pre-launch checklist → Launch timing optimization

Improving Existing App

1. ASO score calculation → Identify gaps → Metadata optimization → A/B testing → Review analysis → Implement changes

International Expansion

1. Localization planning → Market prioritization → Metadata translation → ROI analysis → Phased rollout

Ongoing Optimization

1. Monthly keyword ranking tracking → Quarterly metadata updates → Continuous A/B testing → Review monitoring → Seasonal campaigns

Need Help?

If you need clarification on any aspect of ASO or want to combine multiple analyses, just ask! For example:

Hey Claude—I just added the "app-store-optimization" skill. Can you create a complete ASO strategy for my new productivity app? I need keyword research, optimized metadata for both stores, a pre-launch checklist, and launch timing recommendations.

The skill can handle comprehensive, multi-phase ASO projects as well as specific tactical optimizations.

App Store Optimization (ASO) Skill

Version: 1.0.0 Last Updated: November 7, 2025 Author: Claude Skills Factory

Overview

A comprehensive App Store Optimization (ASO) skill that provides complete capabilities for researching, optimizing, and tracking mobile app performance on the Apple App Store and Google Play Store. This skill empowers app developers and marketers to maximize their app's visibility, downloads, and success in competitive app marketplaces.

What This Skill Does

This skill provides end-to-end ASO capabilities across seven key areas:

1. Research & Analysis: Keyword research, competitor analysis, market trends, review sentiment 2. Metadata Optimization: Title, description, keywords with platform-specific character limits 3. Conversion Optimization: A/B testing framework, visual asset optimization 4. Rating & Review Management: Sentiment analysis, response strategies, issue identification 5. Launch & Update Strategies: Pre-launch checklists, timing optimization, update planning 6. Analytics & Tracking: ASO scoring, keyword rankings, performance benchmarking 7. Localization: Multi-language strategy, translation management, ROI analysis

Key Features

Comprehensive Keyword Research

• Search volume and competition analysis
• Long-tail keyword discovery
• Competitor keyword extraction
• Keyword difficulty scoring
• Strategic prioritization

Platform-Specific Metadata Optimization

• Apple App Store:
• Title (30 chars)
• Subtitle (30 chars)
• Promotional Text (170 chars)
• Description (4000 chars)
• Keywords field (100 chars)
• Google Play Store:
• Title (50 chars)
• Short Description (80 chars)
• Full Description (4000 chars)
• Character limit validation
• Keyword density analysis
• Multiple optimization strategies

Competitor Intelligence

• Automated competitor discovery
• Metadata strategy analysis
• Visual asset assessment
• Gap identification
• Competitive positioning

ASO Health Scoring

• 0-100 overall score
• Four-category breakdown (Metadata, Ratings, Keywords, Conversion)
• Strengths and weaknesses identification
• Prioritized action recommendations
• Expected impact estimates

Scientific A/B Testing

• Test design and hypothesis formulation
• Sample size calculation
• Statistical significance analysis
• Duration estimation
• Implementation recommendations

Global Localization

• Market prioritization (Tier 1/2/3)
• Translation cost estimation
• Character limit adaptation by language
• Cultural keyword considerations
• ROI analysis

Review Intelligence

• Sentiment analysis
• Common theme extraction
• Bug and issue identification
• Feature request clustering
• Professional response templates

Launch Planning

• Platform-specific checklists
• Timeline generation
• Compliance validation
• Optimal timing recommendations
• Seasonal campaign planning

Python Modules

This skill includes 8 powerful Python modules:

1. keyword_analyzer.py

Purpose: Analyzes keywords for search volume, competition, and relevance

Key Functions:

• analyze_keyword(): Single keyword analysis
• compare_keywords(): Multi-keyword comparison and ranking
• find_long_tail_opportunities(): Generate long-tail variations
• calculate_keyword_density(): Analyze keyword usage in text
• extract_keywords_from_text(): Extract keywords from reviews/descriptions

2. metadata_optimizer.py

Purpose: Optimizes titles, descriptions, keywords with character limit validation

Key Functions:

• optimize_title(): Generate optimal title options
• optimize_description(): Create conversion-focused descriptions
• optimize_keyword_field(): Maximize Apple's 100-char keyword field
• validate_character_limits(): Ensure platform compliance
• calculate_keyword_density(): Analyze keyword integration

3. competitor_analyzer.py

Purpose: Analyzes competitor ASO strategies

Key Functions:

• analyze_competitor(): Single competitor deep-dive
• compare_competitors(): Multi-competitor analysis
• identify_gaps(): Find competitive opportunities
• _calculate_competitive_strength(): Score competitor ASO quality

4. aso_scorer.py

Purpose: Calculates comprehensive ASO health score

Key Functions:

• calculate_overall_score(): 0-100 ASO health score
• score_metadata_quality(): Evaluate metadata optimization
• score_ratings_reviews(): Assess rating quality and volume
• score_keyword_performance(): Analyze ranking positions
• score_conversion_metrics(): Evaluate conversion rates
• generate_recommendations(): Prioritized improvement actions

5. ab_test_planner.py

Purpose: Plans and tracks A/B tests for ASO elements

Key Functions:

• design_test(): Create test hypothesis and structure
• calculate_sample_size(): Determine required visitors
• calculate_significance(): Assess statistical validity
• track_test_results(): Monitor ongoing tests
• generate_test_report(): Create comprehensive test reports

6. localization_helper.py

Purpose: Manages multi-language ASO optimization

Key Functions:

• identify_target_markets(): Prioritize localization markets
• translate_metadata(): Adapt metadata for languages
• adapt_keywords(): Cultural keyword adaptation
• validate_translations(): Character limit validation
• calculate_localization_roi(): Estimate investment returns

7. review_analyzer.py

Purpose: Analyzes user reviews for actionable insights

Key Functions:

• analyze_sentiment(): Calculate sentiment distribution
• extract_common_themes(): Identify frequent topics
• identify_issues(): Surface bugs and problems
• find_feature_requests(): Extract desired features
• track_sentiment_trends(): Monitor changes over time
• generate_response_templates(): Create review responses

8. launch_checklist.py

Purpose: Generates comprehensive launch and update checklists

Key Functions:

• generate_prelaunch_checklist(): Complete submission validation
• validate_app_store_compliance(): Check guidelines compliance
• create_update_plan(): Plan update cadence
• optimize_launch_timing(): Recommend launch dates
• plan_seasonal_campaigns(): Identify seasonal opportunities

Installation

For Claude Code (Desktop/CLI)

Project-Level Installation

# Copy skill folder to project
cp -r app-store-optimization /path/to/your/project/.claude/skills/

# Claude will auto-load the skill when working in this project

User-Level Installation (Available in All Projects)

# Copy skill folder to user-level skills
cp -r app-store-optimization ~/.claude/skills/

# Claude will load this skill in all your projects

For Claude Apps (Browser)

1. Use the skill-creator skill to import the skill 2. Or manually import via Claude Apps interface

Verification

To verify installation:

# Check if skill folder exists
ls ~/.claude/skills/app-store-optimization/

# You should see:
# SKILL.md
# keyword_analyzer.py
# metadata_optimizer.py
# competitor_analyzer.py
# aso_scorer.py
# ab_test_planner.py
# localization_helper.py
# review_analyzer.py
# launch_checklist.py
# sample_input.json
# expected_output.json
# HOW_TO_USE.md
# README.md

Usage Examples

Example 1: Complete Keyword Research

Hey Claude—I just added the "app-store-optimization" skill. Can you research keywords for my fitness app? I'm targeting people who want home workouts, yoga, and meal planning. Analyze top competitors like Nike Training Club and Peloton.

What Claude will do:

• Use keyword_analyzer.py to research keywords
• Use competitor_analyzer.py to analyze Nike Training Club and Peloton
• Provide prioritized keyword list with search volumes, competition levels
• Identify gaps and long-tail opportunities
• Recommend primary keywords for title and secondary keywords for description

Example 2: Optimize App Store Metadata

Hey Claude—I just added the "app-store-optimization" skill. Optimize my app's metadata for both Apple App Store and Google Play Store:
- App: FitFlow
- Category: Health & Fitness
- Features: AI workout plans, nutrition tracking, progress photos
- Keywords: fitness app, workout planner, home fitness

What Claude will do:

• Use metadata_optimizer.py to create optimized titles (multiple options)
• Generate platform-specific descriptions (short and full)
• Optimize Apple's 100-character keyword field
• Validate all character limits
• Calculate keyword density
• Provide before/after comparison

Example 3: Calculate ASO Health Score

Hey Claude—I just added the "app-store-optimization" skill. Calculate my app's ASO score:
- Average rating: 4.3 stars (8,200 ratings)
- Keywords in top 10: 4
- Keywords in top 50: 15
- Conversion rate: 3.8%
- Title: "FitFlow - Home Workouts"
- Description: 1,500 characters with 3 keyword mentions

What Claude will do:

• Use aso_scorer.py to calculate overall score (0-100)
• Break down by category (Metadata: X/25, Ratings: X/25, Keywords: X/25, Conversion: X/25)
• Identify strengths and weaknesses
• Generate prioritized recommendations
• Estimate impact of improvements

Example 4: A/B Test Planning

Hey Claude—I just added the "app-store-optimization" skill. I want to A/B test my app icon. My current conversion rate is 4.2%. How many visitors do I need and how long should I run the test?

What Claude will do:

• Use ab_test_planner.py to design test
• Calculate required sample size (based on minimum detectable effect)
• Estimate test duration for low/medium/high traffic scenarios
• Provide test structure and success metrics
• Explain how to analyze results

Example 5: Review Sentiment Analysis

Hey Claude—I just added the "app-store-optimization" skill. Analyze my last 500 reviews and tell me:
- Overall sentiment
- Most common complaints
- Top feature requests
- Bugs needing immediate fixes

What Claude will do:

• Use review_analyzer.py to process reviews
• Calculate sentiment distribution
• Extract common themes
• Identify and prioritize issues
• Cluster feature requests
• Generate response templates

Example 6: Pre-Launch Checklist

Hey Claude—I just added the "app-store-optimization" skill. Generate a complete pre-launch checklist for both app stores. My launch date is March 15, 2026.

What Claude will do:

• Use launch_checklist.py to generate checklists
• Create Apple App Store checklist (metadata, assets, technical, legal)
• Create Google Play Store checklist (metadata, assets, technical, legal)
• Add universal checklist (marketing, QA, support)
• Generate timeline with milestones
• Calculate completion percentage

Best Practices

Keyword Research

1. Start with 20-30 seed keywords 2. Analyze top 5 competitors in your category 3. Balance high-volume and long-tail keywords 4. Prioritize relevance over search volume 5. Update keyword research quarterly

Metadata Optimization

1. Front-load keywords in title (first 15 characters most important) 2. Use every available character (don't waste space) 3. Write for humans first, search engines second 4. A/B test major changes before committing 5. Update descriptions with each major release

A/B Testing

1. Test one element at a time (icon vs. screenshots vs. title) 2. Run tests to statistical significance (90%+ confidence) 3. Test high-impact elements first (icon has biggest impact) 4. Allow sufficient duration (at least 1 week, preferably 2-3) 5. Document learnings for future tests

Localization

1. Start with top 5 revenue markets (US, China, Japan, Germany, UK) 2. Use professional translators, not machine translation 3. Test translations with native speakers 4. Adapt keywords for cultural context 5. Monitor ROI by market

Review Management

1. Respond to reviews within 24-48 hours 2. Always be professional, even with negative reviews 3. Address specific issues raised 4. Thank users for positive feedback 5. Use insights to prioritize product improvements

Technical Requirements

• Python: 3.7+ (for Python modules)
• Platform Support: Apple App Store, Google Play Store
• Data Formats: JSON input/output
• Dependencies: Standard library only (no external packages required)

Limitations

Data Dependencies

• Keyword search volumes are estimates (no official Apple/Google data)
• Competitor data limited to publicly available information
• Review analysis requires access to public reviews
• Historical data may not be available for new apps

Platform Constraints

• Apple: Metadata changes require app submission (except Promotional Text)
• Google: Metadata changes take 1-2 hours to index
• A/B testing requires significant traffic for statistical significance
• Store algorithms are proprietary and change without notice

Scope

• Does not include paid user acquisition (Apple Search Ads, Google Ads)
• Does not cover in-app analytics implementation
• Does not handle technical app development
• Focuses on organic discovery and conversion optimization

Troubleshooting

Issue: Python modules not found

Solution: Ensure all .py files are in the same directory as SKILL.md

Issue: Character limit validation failing

Solution: Check that you're using the correct platform ('apple' or 'google')

Issue: Keyword research returning limited results

Solution: Provide more context about your app, features, and target audience

Issue: ASO score seems inaccurate

Solution: Ensure you're providing accurate metrics (ratings, keyword rankings, conversion rate)

Version History

Version 1.0.0 (November 7, 2025)

• Initial release
• 8 Python modules with comprehensive ASO capabilities
• Support for both Apple App Store and Google Play Store
• Keyword research, metadata optimization, competitor analysis
• ASO scoring, A/B testing, localization, review analysis
• Launch planning and seasonal campaign tools

Support & Feedback

This skill is designed to help app developers and marketers succeed in competitive app marketplaces. For the best results:

1. Provide detailed context about your app 2. Include specific metrics when available 3. Ask follow-up questions for clarification 4. Iterate based on results

Credits

Developed by Claude Skills Factory Based on industry-standard ASO best practices Platform requirements current as of November 2025

License

This skill is provided as-is for use with Claude Code and Claude Apps. Customize and extend as needed for your specific use cases.

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Ready to optimize your app? Start with keyword research, then move to metadata optimization, and finally implement A/B testing for continuous improvement. The skill handles everything from pre-launch planning to ongoing optimization.

For detailed usage examples, see HOW_TO_USE.md.

ASO Best Practices Reference

Optimization strategies for improving app store visibility, conversion, and rankings.

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Table of Contents

• Keyword Optimization
• Metadata Optimization
• Visual Asset Optimization
• Rating and Review Management
• Launch Strategy
• A/B Testing Framework
• Conversion Optimization
• Common Mistakes to Avoid

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Keyword Optimization

Keyword Research Process

1. Brainstorm seed keywords - Core terms users search for 2. Expand with variations - Synonyms, related terms, long-tail 3. Analyze competition - Check difficulty scores 4. Evaluate search volume - Prioritize high-volume terms 5. Test and iterate - Monitor rankings and adjust

Keyword Selection Criteria

Keyword Placement Priority

Long-Tail Keyword Strategy

Long-tail keywords have lower volume but higher conversion:

Formula for keyword priority:

Score = (Volume × 0.3) + (1/Competition × 0.3) + (Relevance × 0.4)

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Metadata Optimization

Title Optimization

Structure Formula:

[Brand Name] - [Primary Keyword] [Secondary Keyword/Benefit]

Examples by category:

Title Optimization Checklist:

• [ ] Primary keyword within first 3 words
• [ ] Brand name is memorable and unique
• [ ] Character count matches platform limit
• [ ] No keyword stuffing
• [ ] Readable and natural sounding

Description Optimization

Full Description Structure:

PARAGRAPH 1: Hook + Primary Benefit (50-100 words)
- Address user pain point
- State main value proposition
- Include primary keyword naturally

PARAGRAPH 2-3: Feature Highlights (100-150 words)
- Top 3-5 features with benefits
- Use bullet points or emojis for scanability
- Include secondary keywords

PARAGRAPH 4: Social Proof (50-75 words)
- Download numbers or ratings
- Press mentions or awards
- User testimonials (summarized)

PARAGRAPH 5: Call to Action (25-50 words)
- Clear next step
- Urgency or incentive
- Reassurance (free trial, no credit card)

Keyword Density Target:

• Primary keyword: 2-3% (8-12 mentions in 4000 chars)
• Secondary keywords: 1-2% each (4-8 mentions each)

Subtitle Optimization (iOS)

Effective Subtitle Formulas:

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Visual Asset Optimization

App Icon Best Practices

Icon Testing Questions: 1. Is it recognizable at 29x29px (smallest iOS size)? 2. Does it stand out in search results? 3. Does it communicate app function? 4. Is it distinct from top 10 category competitors?

Screenshot Optimization

Screenshot Hierarchy:

Caption Best Practices:

• Maximum 5-7 words per caption
• Action-oriented verbs ("Track", "Organize", "Discover")
• Benefit-focused, not feature-focused
• Consistent typography and style

Example Caption Evolution:

Video Preview Strategy

Video Structure (30 seconds):

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Rating and Review Management

Review Response Framework

For Negative Reviews (1-2 stars):

Structure:
1. Acknowledge the issue (1 sentence)
2. Apologize without making excuses (1 sentence)
3. Offer solution or next step (1-2 sentences)
4. Invite direct contact (1 sentence)

Example:
"We're sorry the syncing issues are affecting your experience.
Our team is actively working on a fix for the next update.
In the meantime, please try logging out and back in, which
resolves this for most users. If issues persist, email us at
support@app.com and we'll prioritize your case."

For Positive Reviews (4-5 stars):

Structure:
1. Thank sincerely (1 sentence)
2. Acknowledge specific praise (1 sentence)
3. Encourage continued use or sharing (1 sentence)

Example:
"Thank you for the kind words! We're thrilled the reminder
feature helps you stay organized. If you're enjoying the app,
we'd love if you'd share it with friends who might benefit."

Rating Improvement Tactics

Review Prompt Best Practices

When to prompt:

• After user completes 5+ successful sessions
• After milestone achievement (first task completed, 7-day streak)
• After positive in-app feedback ("Was this helpful? Yes")

When NOT to prompt:

• First session
• After error or crash
• During critical workflow
• More than once per 30 days

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Launch Strategy

Pre-Launch Checklist

4 Weeks Before Launch:

• [ ] Finalize app name and keywords
• [ ] Complete all metadata fields
• [ ] Prepare all visual assets
• [ ] Set up analytics (Firebase, Mixpanel)
• [ ] Create press kit and media assets
• [ ] Build email list for launch notification

2 Weeks Before Launch:

• [ ] Submit for app review
• [ ] Prepare social media content
• [ ] Brief press and influencers
• [ ] Set up review response templates
• [ ] Configure in-app rating prompts

Launch Day:

• [ ] Verify app is live in stores
• [ ] Announce across all channels
• [ ] Monitor reviews and respond quickly
• [ ] Track download velocity
• [ ] Document any issues for Day 2 fix

Update Cadence

Seasonal Optimization

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A/B Testing Framework

Test Prioritization Matrix

Sample Size Calculator

Formula:

Sample Size = (2 × (Z² × p × (1-p))) / E²

Where:
Z = 1.96 (for 95% confidence)
p = baseline conversion rate
E = minimum detectable effect (usually 0.05)

Quick Reference:

Test Duration Guidelines

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Conversion Optimization

Conversion Funnel Metrics

Conversion Optimization Levers

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Common Mistakes to Avoid

Keyword Mistakes

Metadata Mistakes

Visual Asset Mistakes

Launch Mistakes

ASO Workflows

Read this when executing a specific ASO task end to end — keyword research, metadata optimization, competitor analysis, app launch, or A/B testing — including the step-by-step procedures, scoring criteria, placement tables, structure diagrams, and worked before/after examples.

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Keyword Research Workflow

Discover and evaluate keywords that drive app store visibility.

Workflow: Conduct Keyword Research

1. Define target audience and core app functions:

• Primary use case (what problem does the app solve)
• Target user demographics
• Competitive category

2. Generate seed keywords from:

• App features and benefits
• User language (not developer terminology)
• App store autocomplete suggestions

3. Expand keyword list using:

• Modifiers (free, best, simple)
• Actions (create, track, organize)
• Audiences (for students, for teams, for business)

4. Evaluate each keyword:

• Search volume (estimated monthly searches)
• Competition (number and quality of ranking apps)
• Relevance (alignment with app function)

5. Score and prioritize keywords:

• Primary: Title and keyword field (iOS)
• Secondary: Subtitle and short description
• Tertiary: Full description only

6. Map keywords to metadata locations 7. Document keyword strategy for tracking 8. Validation: Keywords scored; placement mapped; no competitor brand names included; no plurals in iOS keyword field

Keyword Evaluation Criteria

Keyword Placement Priority

See: references/keyword-research-guide.md

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Metadata Optimization Workflow

Optimize app store listing elements for search ranking and conversion.

Workflow: Optimize App Metadata

1. Audit current metadata against platform limits:

• Title character count and keyword presence
• Subtitle/short description usage
• Keyword field efficiency (iOS)
• Description keyword density

2. Optimize title following formula:

   [Brand Name] - [Primary Keyword] [Secondary Keyword]

3. Write subtitle (iOS) or short description (Android):

• Focus on primary benefit
• Include secondary keyword
• Use action verbs

4. Optimize keyword field (iOS only):

• Remove duplicates from title
• Remove plurals (Apple indexes both forms)
• No spaces after commas
• Prioritize by score

5. Rewrite full description:

• Hook paragraph with value proposition
• Feature bullets with keywords
• Social proof section
• Call to action

6. Validate character counts for each field 7. Calculate keyword density (target 2-3% primary) 8. Validation: All fields within character limits; primary keyword in title; no keyword stuffing (>5%); natural language preserved

Platform Character Limits

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

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Competitor Analysis Workflow

Analyze top competitors to identify keyword gaps and positioning opportunities.

Workflow: Analyze Competitor ASO Strategy

1. Identify top 10 competitors:

• Direct competitors (same core function)
• Indirect competitors (overlapping audience)
• Category leaders (top downloads)

2. Extract competitor keywords from:

• App titles and subtitles
• First 100 words of descriptions
• Visible metadata patterns

3. Build competitor keyword matrix:

• Map which keywords each competitor targets
• Calculate coverage percentage per keyword

4. Identify keyword gaps:

• Keywords with <40% competitor coverage
• High volume terms competitors miss
• Long-tail opportunities

5. Analyze competitor visual assets:

• Icon design patterns
• Screenshot messaging and style
• Video presence and quality

6. Compare ratings and review patterns:

• Average rating by competitor
• Common praise themes
• Common complaint themes

7. Document positioning opportunities 8. Validation: 10+ competitors analyzed; keyword matrix complete; gaps identified with volume estimates; visual audit documented

Competitor Analysis Matrix

Gap Analysis Template

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App Launch Workflow

Execute a structured launch for maximum initial visibility.

Workflow: Launch App to Stores

1. 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

2. Submit for review (2 weeks before):

• Complete all store requirements
• Verify compliance with guidelines
• Prepare launch communications

3. Configure post-launch systems:

• Set up review monitoring
• Prepare response templates
• Configure rating prompt timing

4. Execute launch day:

• Verify app is live in both stores
• Announce across all channels
• Begin review response cycle

5. Monitor initial performance (days 1-7):

• Track download velocity hourly
• Monitor reviews and respond within 24 hours
• Document any issues for quick fixes

6. Conduct 7-day retrospective:

• Compare performance to projections
• Identify quick optimization wins
• Plan first metadata update

7. Schedule first update (2 weeks post-launch) 8. Validation: App live in stores; analytics tracking; review responses within 24h; download velocity documented; first update scheduled

Pre-Launch Checklist

Launch Timing Considerations

See: references/aso-best-practices.md

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A/B Testing Workflow

Test metadata and visual elements to improve conversion rates.

Workflow: Run A/B Test

1. Select test element (prioritize by impact):

• Icon (highest impact)
• Screenshot 1 (high impact)
• Title (high impact)
• Short description (medium impact)

2. Form hypothesis:

   If we [change], then [metric] will [improve/increase] by [amount]
   because [rationale].

3. Create variants:

• Control: Current version
• Treatment: Single variable change

4. Calculate required sample size:

• Baseline conversion rate
• Minimum detectable effect (usually 5%)
• Statistical significance (95%)

5. Launch test:

• Apple: Use Product Page Optimization
• Android: Use Store Listing Experiments

6. Run test for minimum duration:

• At least 7 days
• Until statistical significance reached

7. Analyze results:

• Compare conversion rates
• Check statistical significance
• Document learnings

8. Validation: Single variable tested; sample size sufficient; significance reached (95%); results documented; winner implemented

A/B Test Prioritization

Sample Size Quick Reference

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 test

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Before/After Examples

Title Optimization

Productivity App:

Fitness App:

Subtitle Optimization (iOS)

Keyword Field Optimization (iOS)

Before (Inefficient - 89 chars, 8 keywords):

task manager, todo list, productivity app, daily planner, reminder app

After (Optimized - 97 chars, 14 keywords):

task,todo,checklist,reminder,organize,daily,planner,schedule,deadline,goals,habit,widget,sync,team

Improvements:

• 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

Keyword Research Guide

Systematic approach to discovering, evaluating, and selecting keywords for app store optimization.

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Table of Contents

• Keyword Research Methodology
• Keyword Evaluation Framework
• Competitor Keyword Analysis
• Keyword Mapping Strategy
• Keyword Tracking and Iteration

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Keyword Research Methodology

Phase 1: Seed Keyword Generation

Start by generating initial keyword ideas from multiple sources.

Source 1: Core App Functions

List every action or problem the app solves:

Example for a task management app:
- Create tasks
- Set reminders
- Track deadlines
- Organize projects
- Collaborate with team
- Plan daily schedule

Source 2: User Language Mapping

Match developer terminology to user searches:

Source 3: App Store Autocomplete

Type seed keywords into App Store/Play Store search and record suggestions:

"todo" → todo list, todo app, todo list app, todolist widget
"task" → task manager, task planner, task list, tasks to do
"remind" → reminder app, reminder, reminders widget, remind me

Source 4: Competitor Analysis

Extract keywords from top 10 competitors in category (detailed in section below).

Phase 2: Keyword Expansion

Expansion Techniques:

Keyword Matrix Template:

Phase 3: Keyword Filtering

Remove irrelevant or low-quality keywords:

Exclusion Criteria:

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Keyword Evaluation Framework

Keyword Scoring Model

Evaluate each keyword on four dimensions:

1. Search Volume (0-100)

2. Competition (0-100, inverted)

3. Relevance (0-100)

4. Conversion Potential (0-100)

Composite Score Calculation

Keyword Score = (Volume × 0.25) + (Competition × 0.25) +
                (Relevance × 0.35) + (Conversion × 0.15)

Score Interpretation:

Keyword Evaluation Worksheet

KEYWORD EVALUATION

Keyword: "task manager app"
Date: [Date]

SCORES:
├── Search Volume: 72/100 (High - ~25,000/month)
├── Competition: 45/100 (Medium - 4.4 avg rating in top 10)
├── Relevance: 95/100 (Exact match to core function)
└── Conversion: 85/100 (Transactional intent)

COMPOSITE SCORE: 74.5/100

RECOMMENDATION: Secondary Priority
- Include in subtitle or short description
- Not competitive enough for title (dominated by Todoist, Any.do)
- Consider long-tail variant: "simple task manager app"

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Competitor Keyword Analysis

Competitor Identification

Step 1: Direct Competitors Apps solving the same problem for the same audience.

Step 2: Indirect Competitors Apps solving related problems or targeting overlapping audiences.

Step 3: Category Leaders Top 10-20 apps by downloads in primary category.

Competitor Keyword Extraction

From App Title:

Competitor: "Todoist: To-Do List & Tasks"
Keywords: todoist, to-do list, tasks, to do

From Subtitle (iOS):

Competitor subtitle: "Task Manager & Planner"
Keywords: task manager, planner

From Description (First 100 words): Identify frequently used terms:

"Todoist is the world's favorite task manager and to-do list app.
Organize work and life, hit your goals, and find productivity..."

Extracted: task manager, to-do list, organize, goals, productivity

Competitor Keyword Matrix

Analysis:

• 100% coverage = Highly competitive, essential keyword
• 60-80% coverage = Important category term
• 40% coverage = Potential differentiator
• <40% coverage = Unique opportunity or irrelevant

Keyword Gap Analysis

Identify keywords competitors miss:

KEYWORD GAP ANALYSIS

Underserved Keywords (Low competitor coverage, decent volume):
1. "daily planner widget" - 2/10 competitors, 5,000 searches
2. "task list for teams" - 3/10 competitors, 3,500 searches
3. "todo with calendar sync" - 1/10 competitors, 2,800 searches

Opportunity Assessment:
- "daily planner widget" → Add widget feature, target keyword
- "task list for teams" → Already have feature, update metadata
- "todo with calendar sync" → Feature gap, add to roadmap

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Keyword Mapping Strategy

Keyword Placement Map

Assign each keyword to specific metadata locations:

KEYWORD PLACEMENT MAP

PRIMARY (Title + Keyword Field):
├── task manager (Score: 82)
├── todo list (Score: 78)
└── planner (Score: 75)

SECONDARY (Subtitle + Short Description):
├── reminder app (Score: 68)
├── daily tasks (Score: 65)
└── organize (Score: 62)

TERTIARY (Full Description):
├── checklist (Score: 55)
├── productivity (Score: 52)
├── schedule (Score: 48)
├── deadline (Score: 45)
└── project management (Score: 42)

iOS Keyword Field Strategy

100 Character Optimization:

STEP 1: List all target keywords
task,manager,todo,list,planner,reminder,organize,daily,checklist,
productivity,schedule,deadline,project,goals,habit,widget,sync,
team,collaborate,notes,calendar

STEP 2: Remove duplicates from title
Title: "TaskFlow - Todo List Manager"
Remove: task, todo, list, manager

STEP 3: Remove plurals
Keep: reminder (not reminders)
Keep: goal (not goals)

STEP 4: Prioritize by score and fit
Final 100 chars:
planner,reminder,organize,daily,checklist,productivity,schedule,
deadline,project,goals,habit,widget,sync,team,collaborate

Character count: 98/100

Android Description Keyword Integration

Natural keyword placement in 4,000 characters:

PARAGRAPH 1 (Hook - 300 chars):
Keywords: task manager, todo list, organize
"TaskFlow is the task manager trusted by 2 million users. Create
your perfect todo list and organize everything that matters..."

PARAGRAPH 2 (Features - 800 chars):
Keywords: reminder, checklist, deadline, project
"Set smart reminders that notify you at the right time. Build
checklists for any project. Never miss a deadline with..."

PARAGRAPH 3 (Benefits - 600 chars):
Keywords: productivity, schedule, goals
"Boost your productivity with proven planning methods. Schedule
your day in minutes. Track goals and celebrate..."

PARAGRAPH 4 (Differentiators - 500 chars):
Keywords: widget, sync, team, collaborate
"Beautiful widgets keep tasks visible. Sync across all devices
instantly. Invite your team to collaborate on..."

Total keyword coverage: 14 keywords naturally integrated

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Keyword Tracking and Iteration

Ranking Tracking Cadence

Keyword Performance Metrics

Iteration Process

Monthly Keyword Audit:

1. EXPORT current rankings
   - List all tracked keywords
   - Record current position
   - Note 30-day trend (up/down/stable)

2. IDENTIFY opportunities
   - Keywords improving but not top 10
   - Keywords declining from previous position
   - New high-volume keywords in category

3. PRIORITIZE changes
   - Boost: Keywords at position 11-20
   - Maintain: Keywords at position 1-10
   - Replace: Keywords at position 50+ with no improvement

4. IMPLEMENT updates
   - Adjust keyword field (iOS)
   - Update description (Android)
   - Modify subtitle if needed

5. DOCUMENT changes
   - Record what changed and why
   - Set reminder for 2-week check-in

Keyword Testing Log Template

KEYWORD TEST LOG

Test ID: KW-2025-001
Date Started: [Date]
Keywords Changed:
  - Added: "habit tracker" (replacing "goals app")
  - Added: "daily routine" (replacing "schedule planner")

Rationale:
- "habit tracker" has 3x volume of "goals app"
- "daily routine" trending up 40% in category

Baseline Rankings:
- "habit tracker": Not ranked
- "daily routine": Position 87

30-Day Results:
- "habit tracker": Position 34 (+53)
- "daily routine": Position 28 (+59)

Conclusion: Test successful - retain new keywords
Next Action: Target subtitle position for "habit tracker"

Operations & Benchmarks

Read this when diagnosing ASO problems, setting performance targets, understanding platform/data constraints, or wiring this skill into App Store Connect, Google Play Console, ASO tools, and analytics platforms. Contains the troubleshooting table, success criteria, platform limitations, proactive triggers, output artifacts, communication standards, related skills, and the full integration matrix.

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Troubleshooting

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Success Criteria

• Conversion Rate (Impression-to-Install): Target 25-30% on iOS and 27-33% on Google Play (2026 cross-category median: 25% iOS, 27.3% Google Play). Productivity and utility apps should aim for 40%+ given category norms
• Keyword Rankings: Maintain 10+ keywords in top-10 positions and 20+ keywords in top-50 positions within your primary market. Track ranking improvements week-over-week after each metadata update
• Rating Quality: Sustain an average rating of 4.5+ stars with 100+ ratings per month. Apps below 4.0 stars experience measurable conversion drops. Aim for 99%+ crash-free rate to protect ratings
• Metadata Utilization: Use 90%+ of available character space in title, subtitle (iOS), short description (Android), and keyword field (iOS). Under-utilized metadata is wasted ranking potential
• A/B Test Velocity: Run at least one store listing experiment per month. Achieve statistical significance (95% confidence) before implementing winners. Target 5-15% conversion lift per successful test cycle
• Localization Coverage: Localize metadata for at least 5 priority markets (US, China, Japan, Germany, UK) with native-speaker keyword research. Localized apps see 15-30% download increases in target markets
• Apple Search Ads Efficiency: Maintain a tap-through rate (TTR) above 5% and cost-per-acquisition (CPA) below category median. In 2026, Apple is expanding search ad inventory with additional inline placements -- optimize for the new Maximize Conversions bidding option

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Platform Limitations

Data Constraints

Platform Behavior

When Not to Use This Skill

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Proactive Triggers

• No keyword optimization in title -- App title is the #1 ranking factor. Include top keyword in title.
• Screenshots don't show value -- Screenshots should tell a benefit story, not just show UI.
• No ratings strategy -- Below 4.0 stars kills conversion. Implement in-app rating prompts at positive moments.
• Description keyword-stuffed -- Natural language with keywords beats keyword stuffing. Target 2-3% density.

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Output Artifacts

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Communication

All output passes quality verification:

• Self-verify: source attribution, assumption audit, confidence scoring
• Output format: Bottom Line first, then What (with confidence), Why, How to Act
• Every finding tagged with confidence level: verified, medium confidence, or assumed

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Related Skills

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Integration Points

Platform Requirements Reference

Technical specifications and metadata requirements for Apple App Store and Google Play Store.

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Table of Contents

• Apple App Store Requirements
• Google Play Store Requirements
• Visual Asset Specifications
• Localization Requirements
• Compliance Guidelines

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Apple App Store Requirements

Metadata Character Limits

Keyword Field Optimization Rules

1. No duplicates - Words in title are already indexed 2. No plurals - Apple indexes both singular and plural forms 3. No spaces after commas - Wastes character space 4. No brand names - Violates App Store guidelines 5. No category names - Already indexed via category selection

Example - Efficient keyword field:

task,todo,checklist,reminder,productivity,organize,schedule,planner,goals,habit

Example - Inefficient keyword field (avoid):

task manager, todo list, productivity app, task tracking

App Store Connect Metadata Fields

Age Rating Content Descriptors

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Google Play Store Requirements

Metadata Character Limits

Description Keyword Strategy

Google Play has no separate keyword field. Keywords are extracted from:

1. App Title - Highest weight, most important 2. Short Description - High weight, visible in search 3. Full Description - Medium weight, use naturally throughout 4. Developer Name - Low weight but indexed

Keyword Density Guidelines:

• Primary keyword: 2-3% density in full description
• Secondary keywords: 1-2% each
• Avoid keyword stuffing (>5% triggers spam detection)

Google Play Console Metadata

Content Rating (IARC)

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Visual Asset Specifications

App Icon Requirements

Apple App Store:

Google Play Store:

Screenshot Requirements

Apple App Store:

• Minimum: 2 screenshots per device
• Maximum: 10 screenshots per device
• Format: PNG or JPG, no alpha channel
• First 3 screenshots are critical (most users don't scroll)

Google Play Store:

• Minimum: 2 screenshots
• Maximum: 8 screenshots
• Format: PNG or JPG
• No transparency or borders

App Preview Video

Apple App Store:

• Duration: 15-30 seconds
• Resolution: Match device screenshot size
• Format: M4V, MP4, MOV
• Frame rate: 30 fps
• Audio: Optional but recommended

Google Play Store:

• YouTube video link only
• No duration limit (recommend under 2 minutes)
• Landscape orientation preferred
• Must not contain age-restricted content

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Localization Requirements

Priority Markets by Revenue

Apple App Store Localization

Supported localizations: 40+ languages

Google Play Store Localization

Supported localizations: 75+ languages

Each locale requires:

• Title (50 chars)
• Short description (80 chars)
• Full description (4,000 chars)
• Screenshots (can reuse or localize)

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Compliance Guidelines

Apple App Store Review Guidelines Summary

Common Rejection Reasons: 1. Bugs and crashes (50%+ of rejections) 2. Broken links or placeholder content 3. Misleading app descriptions 4. Privacy policy missing or incomplete 5. In-app purchase issues

Google Play Developer Policies

Common Suspension Reasons: 1. Policy violation (content, ads, permissions) 2. Repetitive content (clone apps) 3. Impersonation (fake apps) 4. Intellectual property infringement 5. Malicious behavior

Privacy Requirements

Apple (App Tracking Transparency):

• ATT prompt required for tracking
• Privacy nutrition labels mandatory
• Data collection disclosure required

Google (Data Safety):

• Data safety section mandatory
• Data collection and sharing disclosure
• Security practices declaration

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Quick Reference Card

Apple vs Google Comparison

Tool Reference

Read this when invoking the skill's Python scripts — full CLI/library usage, classes, methods, parameters, returns, and convenience functions for all eight ASO tools.

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Scripts

Assets

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keyword_analyzer.py

Type: Python library (imported, not CLI)

Classes:

• KeywordAnalyzer -- Core analysis class

Key Methods:

Convenience Function: analyze_keyword_set(keywords_data) -- Analyzes and ranks a full keyword set in one call.

metadata_optimizer.py

Type: Python library (imported, not CLI)

Classes:

• MetadataOptimizer(platform: str = 'apple') -- Platform must be 'apple' or 'google'

Key Methods:

Convenience Function: optimize_app_metadata(platform, app_info, target_keywords) -- Optimizes title, description, and keyword field in one call.

competitor_analyzer.py

Type: Python library (imported, not CLI)

Classes:

• CompetitorAnalyzer(category: str, platform: str = 'apple')

Key Methods:

Convenience Function: analyze_competitor_set(category, competitors_data, platform='apple') -- Full competitive analysis in one call.

aso_scorer.py

Type: Python library (imported, not CLI)

Classes:

• ASOScorer -- Calculates weighted ASO health score (0-100)

Key Methods:

Weights: metadata_quality 25%, ratings_reviews 25%, keyword_performance 25%, conversion_metrics 25%.

Convenience Function: calculate_aso_score(metadata, ratings, keyword_performance, conversion)

ab_test_planner.py

Type: Python library (imported, not CLI)

Classes:

• ABTestPlanner

Key Methods:

Convenience Function: plan_ab_test(test_type, variant_a, variant_b, hypothesis, baseline_conversion)

review_analyzer.py

Type: Python library (imported, not CLI)

Classes:

• ReviewAnalyzer(app_name: str)

Key Methods:

Convenience Function: analyze_reviews(app_name, reviews) -- Runs sentiment, themes, issues, and feature requests in one call.

launch_checklist.py

Type: Python library (imported, not CLI)

Classes:

• LaunchChecklistGenerator(platform: str = 'both') -- Platform: 'apple', 'google', or 'both'

Key Methods:

Convenience Function: generate_launch_checklist(platform, app_info, launch_date)

localization_helper.py

Type: Python library (imported, not CLI)

Classes:

• LocalizationHelper(app_category: str = 'general')

Key Methods:

Convenience Function: plan_localization_strategy(current_market, budget_level, monthly_downloads)