Suede-owned app-store optimization discipline for keyword fields, titles, subtitles, descriptions, screenshots, ratings context, and competitor listing audits. Use when improving App Store or Google Play visibility or listing conversion from a live app URL and current console evidence. NOT FOR: building or releasing the app (use site-to-ios-app or android-app-factory), creating paid ad assets (use suede-ad-creative), or install-event instrumentation (use suede-analytics).
npx skills add https://github.com/JasonColapietro/suede-creator-skills --skill suede-aso
Analyze App Store and Google Play listings with the Suede ASO scoring system. Fetch
live listing data, score metadata, visuals, and ratings, then produce a
prioritized action plan.
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Apple: apps.apple.com/{country}/app/{name}/id{digits}
Google: play.google.com/store/apps/details?id={package}
If the user gives an app name instead of a URL, search the web for:
site:apps.apple.com "{app name}" or site:play.google.com "{app name}"
Use WebFetch to retrieve the listing page. Extract every available field:
Apple App Store fields:
Google Play fields:
If WebFetch returns incomplete data (stores render client-side), note gaps and
work with what's available. Ask the user to paste missing fields if critical.
WebFetch cannot extract screenshot images or caption text. **Take a screenshot
of the listing page** to get visual data:
messaging quality, preview video presence, feature graphic (Google Play)
listing page
Promotional text (Apple): This 170-char field appears above the description
but is often indistinguishable from it in scraped HTML. If you cannot confirm
its presence, note this and recommend the user check App Store Connect.
Before scoring, classify the app into one of three tiers. This determines how
you interpret "textbook ASO" deviations — a deliberate brand choice by a
household name is not the same as a missed opportunity by an unknown app.
| Tier | Signals | Examples |
| --------------- | ------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------- |
| Dominant | Household name, 1M+ ratings, top-10 in category, near-universal brand recognition. Users search by brand name, not generic keywords. | Instagram, Uber, Spotify, WhatsApp, Netflix |
| Established | Well-known in their category, 100K+ ratings, strong organic installs, recognized brand but not universally known. | Strava, Notion, Duolingo, Cash App, Calm |
| Challenger | Building awareness, <100K ratings, needs discovery through keywords and ASO tactics. Most apps fall here. | Your app, most indie/startup apps |
Dominant apps get adjusted scoring in these areas:
Established apps get partial adjustment:
Challenger apps are scored strictly against textbook ASO best practices — every character, screenshot, and keyword matters.
Key principle: Before docking points, ask: "Is this a mistake or a deliberate
choice by a team that has data I don't?" If the app has 1M+ ratings and a
dedicated ASO team, assume their choices are data-informed unless clearly wrong.
Score each dimension 0-10 using the criteria in references/scoring-criteria.md.
Apply the brand maturity tier adjustments from Phase 1.5.
Reference files for platform specs and benchmarks:
references/apple-specs.md — Official Apple character limits, screenshot/video specs, CPP/PPO rules, rejection triggersreferences/google-play-specs.md — Official Google Play limits, screenshot specs, Android Vitals thresholds, policiesreferences/benchmarks.md — Conversion data, rating impact, video lift, screenshot behavior, CPP/event benchmarks| # | Dimension | Weight | What It Covers |
| --- | -------------------- | ------ | ------------------------------------------------------------------------- |
| 1 | Title & Subtitle | 20% | Character usage, keyword presence, clarity, brand + keyword balance |
| 2 | Description | 15% | First 3 lines, keyword density (Google), CTA, structure, promotional text |
| 3 | Visual Assets | 25% | Screenshot count/quality/messaging, video, icon, feature graphic |
| 4 | Ratings & Reviews | 20% | Average rating, volume, recency, developer responses |
| 5 | Metadata & Freshness | 10% | Category choice, update recency, localization count, data safety |
| 6 | Conversion Signals | 10% | Price positioning, IAP transparency, social proof, download range |
Final score = weighted sum, out of 100.
| Score | Grade | Meaning |
| ------ | ----- | --------------------------------------------------------- |
| 85-100 | A | Well-optimized; focus on A/B testing and iteration |
| 70-84 | B | Good foundation; clear opportunities to improve |
| 50-69 | C | Significant gaps; prioritized fixes will have high impact |
| 30-49 | D | Major optimization needed across multiple dimensions |
| 0-29 | F | Listing needs a complete overhaul |
If the user provides competitor URLs or asks for comparison:
If no competitors are specified, suggest the user provide 2-3 or offer to search
for top apps in their category.
Use the template in references/report-template.md to structure the output.
The report must include:
references/apple-specs.md for full specs, dimensions, and rejection triggersreferences/google-play-specs.md for full specs and policy details| Field | Apple Indexed? | Google Indexed? |
| --------------------- | ---------------- | ---------------------- |
| Title | Yes | Yes (strongest signal) |
| Subtitle / Short desc | Yes | Yes |
| Keyword field | Yes (hidden) | Does not exist |
| Long description | No | Yes (heavily) |
| Screenshot captions | Yes (since 2025) | No |
| In-app events | Yes | N/A (LiveOps instead) |
| Developer name | No | Partial |
| IAP names | Yes | Yes |
Flag these if found. Items marked _(tier-dependent)_ should be evaluated against
the app's brand maturity tier — they may be deliberate choices for Dominant apps.
Always flag (all tiers):
Flag for Challenger/Established only _(not mistakes for Dominant apps):_
Flag for all tiers but note context:
suede-ad-creative.suede-analytics.suede-customer-research.site-to-ios-app or android-app-factory.suede-aso.A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
Take jasoncolapietro/suede-aso from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.