app-store-optimization

Name: app-store-optimization
Availability: InStock
Author: shirulot

Execute keyword research, competitor benchmarking, and metadata refinement for mobile app stores.

Updated Jul 6, 2026

Search Tags:#mobile marketing #keyword research #conversion optimization #competitor analysis #app store #aso

Ready to run

npx skills add https://github.com/shirulot/codex-skill --skill app-store-optimization-shirulot

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: app-store-optimization
Source: https://github.com/shirulot/codex-skill/tree/main/app-store-optimization
Command: npx skills add https://github.com/shirulot/codex-skill --skill app-store-optimization-shirulot

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill solves the complexity of managing mobile app store presence by providing a data-driven framework for keyword research, metadata optimization, and performance tracking across Apple and Google platforms.

Core Features & Use Cases

Comprehensive ASO Toolkit: Perform keyword research, competitor analysis, and A/B testing for visual assets.
Metadata Optimization: Generate platform-specific titles and descriptions that adhere to strict character limits.
Use Case: If your fitness app is struggling to rank for competitive terms, use this skill to identify long-tail keyword opportunities and optimize your store listing to improve your impression-to-install conversion rate.

Quick Start

Use the app-store-optimization skill to research the best keywords for my new productivity app and provide a prioritized list with search volume estimates.

Frequently Asked Questions about app-store-optimization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I do App Store Optimization for both Apple and Google platforms?▼

App Store Optimization across Apple and Google platforms involves executing keyword research, competitor benchmarking, metadata refinement, and A/B testing. This framework calculates ASO health scores to enhance organic discovery and impression-to-install conversion rates.

How do I find long-tail keywords for my mobile app to improve discovery?▼

Finding long-tail keywords for mobile apps requires data-driven keyword research and competitor analysis. By identifying less competitive search terms and refining metadata, you can improve organic discovery and target high-intent users effectively.

Does App Store Optimization support A/B testing for visual assets?▼

App Store Optimization supports A/B testing for visual assets to validate performance. It utilizes Python-based analysis modules to benchmark competitor assets and calculate ASO health scores, ensuring optimized store listings.

How do I generate platform-specific app store titles that adhere to character limits?▼

Generating platform-specific app store titles requires metadata optimization that strictly adheres to Apple and Google character limits. This process refines titles and descriptions to maximize visibility while maintaining store compliance.

Can I use Python to validate app store compliance and calculate ASO health scores?▼

You can use Python-based analysis modules to validate store compliance and calculate ASO health scores. This data-driven framework executes competitor benchmarking and metadata refinement to track mobile app performance accurately.

What is the best way to increase my mobile app impression-to-install conversion rate?▼

Increasing your mobile app impression-to-install conversion rate requires comprehensive App Store Optimization. This involves A/B testing visual assets, refining metadata, and executing competitor analysis to improve overall organic discovery.