| name | aso-optimizer |
| description | App Store Optimization toolkit for iOS and Android apps. Fetches live app metadata from the iTunes Search API, validates character limits, scores metadata quality against best practices, and compares with competitor apps. Use when the user mentions ASO, app store optimization, app metadata, app title optimization, app store listing improvement, Google Play or Play Store optimization, or Android app listing improvement.
|
ASO Optimizer Skill
App Store Optimization toolkit that helps improve app visibility and conversion
rates on the Apple App Store and Google Play Store.
First Run
When a user runs /aso-optimizer analyze <app>,
display this intro before starting:
"""
🔍 ASO Optimizer
What I'll do:
Search the iTunes API for "[app name]" and score the listing
against ASO best practices. Then fetch top 5 competitors for comparison.
What you'll get:
→ ASO health score (0-100)
→ Metadata quality breakdown (title, description, ratings, completeness)
→ Competitor comparison
→ Prioritized optimization suggestions
Note: Uses the free iTunes Search API. Keyword volume and download
estimates require optional API keys (see SKILL.md for details).
Output: Saved to ASO-REPORT.md
Time: ~30 seconds.
Searching...
"""
Then proceed immediately.
Commands
/aso-optimizer analyze <app-name>
Fetch live app metadata from the iTunes Search API and score it against ASO
best practices.
Example:
/aso-optimizer analyze "Slack"
/aso-optimizer validate
Validate metadata fields against platform-specific character limits for iOS,
Android, or both.
Report: Save output to ASO-VALIDATION-REPORT.md
Example:
/aso-optimizer validate
/aso-optimizer compare <app1> <app2>
Side-by-side metadata comparison between two apps. Highlights strengths and
weaknesses of each listing.
Report: Save output to ASO-COMPARE-REPORT.md
Example:
/aso-optimizer compare "Slack" "Microsoft Teams"
/aso-optimizer score
Calculate a detailed ASO health score (0-100) with a breakdown across four
weighted categories.
Report: Save output to ASO-SCORE-REPORT.md
Example:
/aso-optimizer score
/aso-optimizer optimize
Generate improved metadata suggestions based on the current listing analysis
and competitor benchmarks.
Report: Save output to ASO-OPTIMIZE-REPORT.md
Example:
/aso-optimizer optimize
Full Analyze Flow
When running the analyze command, the skill follows this sequence:
- Fetch live data - Query the iTunes Search API for the target app
(
https://itunes.apple.com/search?term={app_name}&entity=software&country=us&limit=10,
preferring an exact name match among the results)
- Evaluate metadata - Compare metadata against best practices including
title keyword placement, description structure, ratings health, and
screenshot count
- Fetch competitors - Pull the top 5 competitor apps in the same primary
category for benchmarking
- Calculate ASO health score - Generate a weighted score from 0 to 100
- Generate recommendations - Produce prioritized, actionable suggestions
for improving the listing
- Generate report - Save the complete analysis to
ASO-REPORT.md in the
current working directory
Output Rules (MANDATORY)
File Output
Chat Output
After saving, show a SHORT summary in chat (max 10 lines):
"""
✅ ASO analysis complete - saved to ASO-REPORT.md
App: [App Name]
ASO Health Score: [X]/100 ([interpretation])
Top findings:
- [Most impactful metadata issue]
- [Second issue]
- [Third issue]
Full report with competitor comparison and keyword strategy → open ASO-REPORT.md
"""
NEVER dump the full report in chat. The file is the deliverable.
ASO Health Score Breakdown
The health score is calculated across four weighted categories:
| Category | Weight | What It Measures |
|---|
| Title Optimization | 30% | Keyword presence, character length usage, brand-keyword balance |
| Description Quality | 25% | Length (ideal 2000-4000 chars), structural formatting, keyword density, call-to-action presence |
| Ratings Health | 25% | Average rating (4.0+ good, 4.5+ great), total rating count, recent review sentiment |
| Metadata Completeness | 20% | All fields populated, subtitle utilized, keyword field maximized, screenshots present |
Score Ranges
- 90-100: Excellent - App listing is highly optimized
- 70-89: Good - Minor improvements possible
- 50-69: Needs Work - Several optimization opportunities exist
- 30-49: Poor - Significant gaps in metadata strategy
- 0-29: Critical - Listing needs a complete overhaul
Metadata Best Practices
Title (30 characters max)
- Place the highest-value keyword after the brand name
- Use the full 30 characters when possible
- Format:
Brand - Primary Keyword or Brand: Primary Keyword
Subtitle (iOS only, 30 characters)
- Include secondary keywords not in the title
- Describe the core value proposition
- Avoid repeating title keywords
Keywords Field (iOS only, 100 characters)
- Use commas to separate terms, no spaces after commas
- Never repeat words already in the title or subtitle
- Prioritize single words over phrases (the system combines them)
- Use all 100 characters
Description (4,000 characters max)
- Front-load the first 3 lines (visible before "Read More")
- Use line breaks and bullet points for readability
- Include keywords naturally - not stuffed
- End with a clear call-to-action
Ratings and Reviews
- Aim for 4.0+ average rating
- Higher rating counts build trust
- Respond to negative reviews promptly
- Use in-app review prompts strategically
Platform Character Limits Reference
| Field | Apple App Store | Google Play Store |
|---|
| App Name/Title | 30 chars | 30 chars |
| Subtitle | 30 chars | N/A |
| Short Description | N/A | 80 chars |
| Keywords Field | 100 chars | N/A |
| Promotional Text | 170 chars | N/A |
| Full Description | 4,000 chars | 4,000 chars |
| What's New | 4,000 chars | 500 chars |
| Developer Name | 50 chars | varies |
Scripts
scripts/metadata_validator.py
Validates metadata fields against platform character limits. Accepts a metadata
dictionary and platform target (ios, android, or both). In "both" mode each
platform is validated separately with per-platform result rows (e.g.
whats_new (ios) vs whats_new (android)). Returns pass/fail status and
remaining character counts per field.
Run:
python3 scripts/metadata_validator.py --platform both --file metadata.json
python3 scripts/metadata_validator.py --platform ios --file metadata.json
python3 scripts/metadata_validator.py --demo
scripts/aso_scorer.py
Fetches app data from the iTunes Search API and calculates an ASO health score.
Accepts an app name string or a pre-built metadata dictionary. Returns a score
breakdown, competitor comparison, and prioritized recommendations.
Run:
python3 scripts/aso_scorer.py "App Name"
python3 scripts/aso_scorer.py "App Name" --country us --no-competitors --json
python3 scripts/aso_scorer.py --demo
API Integrations (Optional)
This skill works out of the box with the free iTunes Search API. However, the free API does not provide keyword search volume, keyword difficulty scores, or download estimates.
If the user provides their own API keys, use them for deeper ASO intelligence.
| Environment Variable | Service | What It Unlocks |
|---|
APPSTORE_CONNECT_KEY_ID + APPSTORE_CONNECT_ISSUER_ID + APPSTORE_CONNECT_KEY_PATH | App Store Connect API | Real download counts, conversion rates, keyword rankings, A/B test results |
SENSOR_TOWER_API_KEY | Sensor Tower API | Keyword search volume, keyword difficulty scores, download estimates, category rankings |
Other active commercial ASO platforms with APIs include AppTweak and
AppFigures. (data.ai, formerly App Annie, was acquired by Sensor Tower in
2024 and is no longer a separate service.)
How to set up:
export APPSTORE_CONNECT_KEY_ID="your_key_id"
export APPSTORE_CONNECT_ISSUER_ID="your_issuer_id"
export APPSTORE_CONNECT_KEY_PATH="/path/to/AuthKey.p8"
export SENSOR_TOWER_API_KEY="your_api_key"
Behavior:
- If API keys are set → Enrich the analysis with keyword volume, downloads, and market data
- If not set → Use free iTunes Search API (current default behavior, no change)
- Each integration is independent - you can set one without the others
When data is limited: If the analysis cannot provide keyword volume, download estimates, or ranking data, inform the user which API keys would unlock these. Example:
ℹ️ Keyword search volume and difficulty data unavailable - using metadata quality analysis only. For keyword intelligence, set SENSOR_TOWER_API_KEY. For download and conversion data, set APPSTORE_CONNECT_KEY_ID. See the API Integrations section in this skill's SKILL.md for setup instructions.
Limitation
This skill uses the free iTunes Search API for live app data by default. Without
optional API integrations above, it does not provide keyword search volume,
keyword difficulty scores, or download estimates. It focuses on what is freely
measurable: metadata quality, best practice compliance, and competitor metadata
comparison.
References
references/aso-checklist.md - Pre-launch and post-launch ASO checklists
references/keyword-strategy.md - Keyword research and placement strategy
references/metadata-limits.md - Detailed platform character limits