Complete App Store Optimization (ASO) toolkit for mobile app performance on Apple App Store and Google Play Store. Use to research keywords, optimize metadata, analyze competitors, and calculate ASO health scores.
This skill provides specialized tools and workflows for optimizing mobile applications for discoverability and conversion on major app stores.
Analyze search volume, competition, and relevance to identify high-potential keywords.
scripts/keyword_analyzer.pyGenerate and validate store listings (Title, Description, Keywords) against platform-specific constraints.
scripts/metadata_optimizer.pyDeep-dive into top-performing apps to identify gaps and strategy overlaps.
scripts/competitor_analyzer.pyscripts/lib/itunes_api.py for real-time Apple data.Calculate an overall ASO health score (0-100) based on metadata quality, ratings, and keyword performance.
scripts/aso_scorer.pycompetitive, niche, and utility benchmarks.apple vs google.Generate human-readable ASO audits and market overviews.
--format markdown for visual dashboards.scripts/review_analyzer.py.scripts/ab_test_planner.py.scripts/localization_helper.py.{
"metadata": {"title_length": 30, "description_length": 2500},
"ratings": {"average_rating": 4.5, "total_ratings": 1000},
"keyword_performance": {"top_10": 5},
"conversion": {"impression_to_install": 0.05},
"platform": "apple",
"category_context": "competitive"
}
Run python3 scripts/aso_scorer.py --format markdown < input.json to get a visual health dashboard.
Ask Gemini: "Analyze the Productivity market on the App Store. Show me a formatted report with competitor rankings and keyword gaps."
Gemini will use scripts/competitor_analyzer.py --format markdown to generate the report.
keyword_analyzer.py: Main keyword engine.metadata_optimizer.py: Field-specific optimization and validation.aso_scorer.py: Comprehensive health scoring.competitor_analyzer.py: Market analysis tool.lib/: Contains itunes_api.py (official API wrapper) and scraper.py (WebFetch utilities).config.json: Master Configuration. Contains all genre mappings and category-specific benchmarks (Competitive, Niche, Utility).sample_input.json: Template for tool inputs.expected_output.json: Schema for tool responses.agents.md: Documentation on agent-coordinated workflows.iTunesAPI for Apple data before falling back to scraping.category_context (e.g., competitive) for more accurate scoring and tailored recommendations.country parameter for international market research (supports all ISO codes).--format markdown flag when you need a visual summary for the user.