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app-store-optimization

App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.

94

1.18x
Quality

92%

Does it follow best practices?

Impact

95%

1.18x

Average score across 6 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Evaluation results

100%

7%

iOS App Store Listing Optimization for a Budgeting App

iOS keyword field optimization

Criteria
Without context
With context

No plurals in keyword field

60%

100%

No spaces after commas

100%

100%

No title duplicates in keyword field

100%

100%

Keyword field within 100 chars

100%

100%

Title follows formula

100%

100%

Keyword scoring provided

100%

100%

Placement tiers applied

100%

100%

Description has hook paragraph

100%

100%

Description has social proof section

62%

100%

Description has call to action

100%

100%

No keyword stuffing

100%

100%

No competitor brand names

100%

100%

95%

2%

Competitive Keyword Landscape Analysis for a Meditation App

Competitor keyword gap analysis

Criteria
Without context
With context

10+ competitors analyzed

100%

100%

Competitor categorization

100%

100%

Keyword matrix present

100%

100%

Coverage percentages calculated

100%

100%

Gaps use <40% threshold

100%

100%

Long-tail opportunities included

100%

100%

15+ keywords in matrix

100%

100%

Keyword sources from metadata

62%

100%

Visual/messaging audit present

100%

100%

No competitor brand names as targets

100%

100%

Volume estimates included

50%

37%

100%

15%

Conversion Optimization Testing Plan for a Language Learning App

A/B test planning and documentation

Criteria
Without context
With context

Single variable per test

70%

100%

Hypothesis formula used

50%

100%

Correct sample size for 2% CVR

58%

100%

Minimum 7-day duration stated

100%

100%

95% significance threshold

100%

100%

iOS tool identified correctly

100%

100%

Android tool identified correctly

100%

100%

Icon tested first

100%

100%

Results log template included

77%

100%

Invalid test constraints noted

100%

100%

90%

21%

Launch Planning for FreshRoute Travel App

App launch timeline planning

Criteria
Without context
With context

4-week pre-launch prep

100%

100%

Analytics tools named

100%

100%

Submission 2 weeks before launch

0%

100%

Launch day is Tuesday or Wednesday

0%

100%

Hourly download velocity tracking

100%

0%

24-hour review response

100%

100%

7-day retrospective

70%

100%

First update 2 weeks post-launch

20%

100%

Pre-launch checklist categories

100%

100%

Launch day verification steps

100%

100%

94%

2%

Optimize Store Listings for BudgetWise Finance App

App description structure and metadata optimization

Criteria
Without context
With context

Title follows brand-keyword formula

100%

100%

iOS title within 30 chars

100%

100%

Android title within 50 chars

100%

100%

iOS subtitle within 30 chars

100%

100%

iOS subtitle has action verb

0%

25%

Android short description within 80 chars

100%

100%

Description hook addresses pain point

100%

100%

Description has social proof section

100%

100%

Description has call to action

100%

100%

Keyword density 2-3% primary

100%

100%

No keyword stuffing above 5%

100%

100%

Description features section uses bullets

100%

100%

93%

44%

Keyword Strategy for MindfulMoments Meditation App

Keyword research scoring and placement strategy

Criteria
Without context
With context

15+ candidate keywords

100%

100%

Four scoring dimensions present

100%

100%

Relevance weight 35%

0%

100%

Volume and competition weights 25% each

0%

100%

Conversion weight 15%

0%

100%

Three placement tiers assigned

60%

90%

iOS keyword field has no plurals

0%

100%

No competitor brand names targeted

30%

40%

User language not developer terminology

100%

100%

Exclusion rationale provided

100%

100%

Long-tail keywords included

100%

100%

Repository
alirezarezvani/claude-skills
Evaluated
Agent
Claude Code
Model
Claude Sonnet 4.6

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