App Store Optimisation (Codex)

Overview

Provide end-to-end ASO support for App Store and Play Store listings, from research to execution. Use bundled Python modules for structured analysis and planning, and use browsing or user-provided inputs for live data.

Quick Start

1. Identify the task: keyword research, metadata optimization, competitor analysis, review analysis, ASO scoring, A/B testing, localization, or launch planning.
2. Request required inputs (platforms, markets, current metadata, target keywords, metrics).
3. Use the matching script from scripts/ to generate analysis or plans.
4. Validate character limits and platform rules, then deliver actionable recommendations.

Core Tasks

Keyword research

Use scripts/keyword_analyzer.py.

Request:

• Candidate keywords
• Estimated search volume and competition (user-provided or inferred)
• Relevance score per keyword

Deliver:

• Ranked keywords (primary, secondary, long-tail)
• Difficulty and potential scores

Metadata optimisation

Use scripts/metadata_optimizer.py.

Request:

• Current metadata (title, subtitle, descriptions)
• Target keywords and value proposition
• Platform(s) and markets

Deliver:

• Optimized titles and descriptions with character counts
• Keyword density guidance

Default character limits (verify current limits before final output):

• Apple App Store: title 30, subtitle 30, promo text 170, description 4000, keywords 100
• Google Play: title 50, short description 80, full description 4000

Competitor analysis

Use scripts/competitor_analyzer.py.

Request:

• Competitor names or IDs
• Platform and market

Optional data collection:

• Use scripts/itunes_api.py for Apple metadata
• Use browsing with prompt templates from scripts/scraper.py

Deliver:

• Keyword overlap, metadata patterns, visual asset notes, and gaps

Review analysis

Use scripts/review_analyzer.py.

Request:

• Review text, ratings, and date range

Deliver:

• Sentiment split, top issues, feature requests, response templates

ASO scoring

Use scripts/aso_scorer.py.

Request:

• Metadata quality inputs, ratings data, keyword ranking counts, conversion metrics

Deliver:

• Overall score with category breakdown and prioritized recommendations

A/B testing

Use scripts/ab_test_planner.py.

Request:

• Baseline conversion rate and traffic
• Variants and test goal

Deliver:

• Sample size, duration guidance, and success metrics

Localization planning

Use scripts/localization_helper.py.

Request:

• Current markets and target locales
• Budget and priority markets

Deliver:

• Localization priority order and draft localized metadata

Launch and update checklists

Use scripts/launch_checklist.py.

Request:

• Platform(s), launch date, category, and key features

Deliver:

• Pre-launch checklist and post-launch monitoring plan

Data Sources

See references/data_sources.md for API and browsing guidance.

Resources

scripts/

• keyword_analyzer.py
• metadata_optimizer.py
• competitor_analyzer.py
• review_analyzer.py
• aso_scorer.py
• ab_test_planner.py
• localization_helper.py
• launch_checklist.py
• itunes_api.py
• scraper.py

references/

• data_sources.md
• sample_input.json
• expected_output.json