LaunchKit · 2026
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app-store-optimization

App Store Optimization toolkit.

4
2.1k downloads
by @alirezarezvani

Setup & Installation

openclaw skills install @alirezarezvani/app-store-optimization

Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:

npx clawhub install app-store-optimization

Version History

v2.1.1Mar 9, 2026 - Version note by skill developer:

v2.1.1: optimization, reference splits

What This Skill Does

ASO toolkit for Apple App Store and Google Play Store. Covers keyword research and scoring, metadata optimization, competitor gap analysis, A/B test planning, and structured launch workflows. Works with platform-specific character limits and placement rules for both iOS and Android.

Combines keyword scoring, competitor gap analysis, and platform character limits into one structured workflow instead of maintaining separate spreadsheets or switching between tools.

When to use it

  • Rewriting an app title and keyword field before submitting an update
  • Finding keyword gaps by analyzing top competitor listings
  • Planning an A/B test for a new app icon or first screenshot
  • Generating a platform-specific launch checklist before store submission
  • Auditing an existing listing for keyword stuffing or character limit violations

Example Workflow

Here's how your AI assistant might use this skill in practice.

INPUT

User asks: Optimize my fitness app's App Store listing

AGENT
  1. 1Audit current title, subtitle, keyword field, and description against iOS character limits
  2. 2Generate seed keywords from app features and user language, score each by volume, competition, and relevance
  3. 3Rewrite the title using the [Brand] - [Primary Keyword] [Secondary Keyword] formula within 30 characters
  4. 4Optimize the keyword field by removing title duplicates, stripping plurals, and eliminating spaces after commas
  5. 5Rewrite the description with a pain-point hook, feature bullets with secondary keywords, social proof, and a call to action
OUTPUT

Rewritten metadata with keyword placements mapped per field, character counts validated, and keyword density within the 2-3% target