Aso conversion

Skill FelixGraeber/claude-aso-audit-skill/skills/aso-conversion

ASO audit skill pack for Claude Code: audit App Store and Google Play listings, keywords, metadata, visuals, reviews, and competitors.

Install

npx -y skills add FelixGraeber/claude-aso-audit-skill --skill aso-conversion

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Conversion rate optimization for app store listings. Analyzes first-impression elements, screenshot narrative, social proof signals, and psychology-based messaging to maximize install rate. Triggers on: "conversion", "install rate", "CRO", "conversion rate".

SKILL.md

3.2 KB, as published. Nobody here has run it

ASO Conversion — Conversion Rate Optimization

Capabilities

First-impression audit (what users see before tapping "Read More")
Screenshot narrative arc analysis
Social proof signal assessment
Psychology-based messaging evaluation
Category conversion benchmarking
Conversion funnel analysis (impression → page view → install)

Conversion Benchmarks (2024-2025)

Platform	Average Conversion
iOS App Store	~25%
Google Play	~27%

Category variance is significant (10-115%+ range).

First-Impression Elements

What users see WITHOUT scrolling or tapping "Read More":

iOS Search Results

App icon
App name
Subtitle
Rating (stars + count)
First 3 screenshots (CRITICAL)
Price / "Get" button

Google Play Search Results

App icon
App title
Developer name
Rating (stars)
Price / "Install" button

Full Listing (Above Fold)

Icon + name + developer
Rating + review count
Screenshots (scrollable)
Short description (Android) / first 3 lines of description (iOS)

Scoring (0-100)

Factor	Weight	What to assess
First 3 screenshots	25%	Clear value prop, hook, visual quality
Title clarity	20%	Does it explain what the app does?
Rating strength	20%	≥4.5 = strong, ≥4.0 = acceptable, <4.0 = hurting
Social proof	15%	Review count, awards, editor's choice, download count
Subtitle/short desc	10%	Benefit-oriented, compelling
Icon appeal	10%	Distinctive, professional, recognizable

Psychology Triggers to Evaluate

Social proof: High rating, large review count, "X million users"
Authority: Awards, press mentions, editor's choice badges
Loss aversion: "Don't miss out", limited features in free tier
Specificity: Concrete numbers ("Track 50+ habits") vs vague claims
Benefit framing: Focus on outcomes, not features

Output Format

# Conversion Analysis: [App Name]

## Score: XX/100

## First-Impression Audit
| Element | Current | Assessment | Recommendation |
|---------|---------|-----------|----------------|
| Icon | [description] | [score] | [improvement] |
| Title | "[current]" | [score] | [improvement] |
| Subtitle/Short Desc | "[current]" | [score] | [improvement] |
| Rating | X.X (Y reviews) | [score] | [improvement] |
| Screenshot 1 | [description] | [score] | [improvement] |
| Screenshot 2 | [description] | [score] | [improvement] |
| Screenshot 3 | [description] | [score] | [improvement] |

## Screenshot Narrative Analysis
[Flow assessment: hook → features → proof]

## Social Proof Signals
[What's present, what's missing]

## Psychology Triggers
[Which are used, which could be added]

## Quick Wins
[Highest-impact, lowest-effort changes]

Available Tools

Read, Bash, Write, Glob, Grep