菜单
A/B testing strategy for iOS Product Page Optimization (PPO) and Android Store Listing Experiments. Hypothesis design, variant creation, statistical significance guidance. Triggers on: "A/B test", "experiment", "PPO", "product page optimization", "store listing experiments".
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基于 SOC 职业分类
Comprehensive App Store Optimization for iOS and Android apps. Full listing audits with parallel subagents, keyword research, metadata optimization, visual asset analysis, review management, competitor intelligence, localization, A/B testing, technical ASO, and conversion rate optimization.
Apple App Store Connect API integration. Fetch iOS app metadata, reviews, ratings, and version info directly from App Store Connect. Requires API key. Triggers on: "app store connect", "asc".
Live ASO data via AppTweak REST API. Keyword suggestions with volume/difficulty, app rankings, competitor analysis, review sentiment, and historical data. Requires AppTweak API key. Triggers on: "apptweak", "live data", "keyword volume".
Full app listing audit with parallel subagent delegation. Scores listing across core ASO categories (0-100), flags problems, generates prioritized action plan. Works in local mode (auto-detect Fastlane/Xcode/Gradle metadata) or remote mode (fetch live listing by app ID). Triggers on: "audit", "full ASO check", "analyze my app", "listing health check".
Visual asset analysis for app store listings. Screenshots, app icon, preview videos. Evaluates composition, narrative flow, text readability, platform compliance, and conversion impact. Triggers on: "screenshots", "icon", "preview video", "visual assets".
Store policy compliance checker for iOS App Store and Google Play. Validates metadata against Apple App Store Review Guidelines and Google Play Developer Program Policies. Catches violations that would cause rejection. Also validates ASO recommendations from other agents. Triggers on: "compliance", "policy check", "guidelines", "store policies", "review guidelines", "will this get rejected", "is this allowed".
| name | aso-ab-testing |
| description | A/B testing strategy for iOS Product Page Optimization (PPO) and Android Store Listing Experiments. Hypothesis design, variant creation, statistical significance guidance. Triggers on: "A/B test", "experiment", "PPO", "product page optimization", "store listing experiments". |
| user-invokable | true |
| argument-hint | <app-id> [--element icon|screenshots|description] |
| Aspect | Specification |
|---|---|
| Testable elements | App icon, screenshots, app preview video |
| NOT testable | Title, subtitle, keywords, description |
| Max treatments | 3 (plus original) |
| Traffic split | Apple-controlled |
| Min duration | 7 days recommended |
| Max duration | 90 days |
| Audience | All users or specific locales |
| Active tests | 1 at a time (on default product page) |
| Aspect | Specification |
|---|---|
| Testable elements | Icon, feature graphic, screenshots, short description, full description, promo video |
| Max experiments | 5 localized + 1 main simultaneously |
| Traffic split | Configurable |
| Min duration | 7 days recommended |
| Audience | Default or country-specific listings |
State: "Changing [element] from [current] to [proposed] will [increase/decrease] [metric] because [reason]."
# A/B Test Plan: [App Name]
## Test 1: [Element Being Tested]
- Hypothesis: [statement]
- Platform: iOS PPO / Android Experiment
- Control: [current element description]
- Treatment: [proposed change]
- Expected impact: [conversion increase estimate]
- Duration: [recommended days]
- Success criteria: [metric + threshold]
## Test Roadmap (Sequential)
1. [highest impact test first]
2. [second test]
3. [third test]
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