Suede ASO Audit

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.

Before Auditing

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.

Phase 1: Identify Store & Fetch

Detect store type from URL

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}"

Fetch the listing

Use WebFetch to retrieve the listing page. Extract every available field:

Apple App Store fields:

• App name (title): 30 char limit
• Subtitle: 30 char limit
• Description (long): not indexed for search, but matters for conversion
• Promotional text: 170 chars, updatable without new release
• Category (primary + secondary)
• Screenshots (count, order, caption text)
• Preview video (presence, duration)
• Rating (average + count)
• Recent reviews (visible ones)
• Price / in-app purchases
• Developer name
• Last updated date
• Version history notes
• Age rating
• Size
• Languages / localizations listed
• In-app events (if any visible)

Google Play fields:

• App name (title): 30 char limit
• Short description: 80 char limit
• Full description: 4,000 char limit, IS indexed for search
• Category + tags
• Feature graphic (presence)
• Screenshots (count, order)
• Preview video (presence)
• Rating (average + count)
• Recent reviews (visible ones)
• Price / in-app purchases
• Developer name
• Last updated date
• What's new text
• Downloads range
• Content rating
• Data safety section
• Languages listed

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.

Visual asset assessment

WebFetch cannot extract screenshot images or caption text. Take a screenshot of the listing page to get visual data:

1. Navigate to the listing URL and capture a full-page screenshot
2. Assess the screenshot for: icon quality, screenshot count, caption text, messaging quality, preview video presence, feature graphic (Google Play)
3. If browser tools are unavailable, ask the user to share a screenshot of the 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.

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Phase 1.5: Assess Brand Maturity

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 definitions

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

Classification happens here, before any scoring. The per-dimension adjustments each tier earns live under "Brand Maturity Adjustments" in references/scoring-criteria.md, which Phase 2 loads before scoring: do not restate or re-derive them here.

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.

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Phase 2: Score Each Dimension

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 triggers
• references/google-play-specs.md: Official Google Play limits, screenshot specs, Android Vitals thresholds, policies
• references/benchmarks.md: Conversion data, rating impact, video lift, screenshot behavior, CPP/event benchmarks

Dimensions and Weights

#	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 of the dimensions that were actually observed.

Unassessable dimensions (read before computing any score)

references/scoring-criteria.md defines score 0 as "cannot assess (data unavailable)". Missing data is the normal case here, not the exception: WebFetch cannot extract screenshots or caption text, and promotional text is indistinguishable in scraped HTML. A 0 for unfetched data is not a bad listing; scoring it as one fabricates a failing grade (an unobserved Visual Assets dimension at 25% weight silently drops an A listing to D).

House rule:

1. A dimension you could not observe is excluded from the weighted denominator, not scored 0. Rescale the remaining weights and state the denominator used ("74/100 across 4 dimensions carrying 75% weight").
2. List every excluded dimension as not assessed, with the reason and what the user would need to supply to close it (a screenshot of the listing page, App Store Connect access).
3. If more than 25% of total weight is unassessed, withhold the letter grade entirely. Report the partial scores and the blocked dimensions instead; do not present a grade the evidence cannot support.

Score interpretation

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

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Phase 3: Competitor Comparison (Optional)

If the user provides competitor URLs or asks for comparison:

1. Fetch 2-3 top competitors in the same category
2. Run the same scoring on each
3. Build a comparison table highlighting where the user's app is weaker/stronger
4. Identify keyword gaps: terms competitors rank for that the user's app doesn't target

If no competitors are specified, suggest the user provide 2-3 or offer to search for top apps in their category.

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Phase 4: Generate Report

Use the template in references/report-template.md to structure the output.

The report must include:

1. Score card: table with all 6 dimensions, scores, the weighted denominator actually used, and the grade (withheld per the unassessable-dimension rule when more than 25% of weight went unassessed)
2. Top 3 quick wins: changes that take <1 hour and have highest impact
3. Detailed findings: per-dimension breakdown with specific issues and fixes
4. Keyword suggestions: based on title/description analysis and competitor gaps
5. Visual asset recommendations: specific screenshot/video improvements
6. Priority action plan: ordered list of changes by impact vs effort

Report rules

• Every recommendation must be specific and actionable ("Change subtitle from X to Y" not "Improve subtitle")
• Include character counts for all text recommendations
• Flag platform-specific differences (Apple vs Google) when relevant
• Note what CANNOT be assessed without paid tools (search volume, exact rankings)
• When suggesting keyword changes, explain WHY each keyword matters

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Platform-Specific Rules

Character limits, screenshot and video specs, CPP and experiment rules, policy prohibitions, Android Vitals thresholds, editorial curation, and rejection triggers are versioned in the three reference files listed in Phase 2. Read the one for the store being audited before scoring any dimension against a spec: they are the source of truth, and dated platform facts are not repeated here.

The one comparison that drives scoring on every audit stays inline:

What Apple Indexes vs What Google Indexes

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

Pre-Launch Metadata Mode

Use this mode when the app has no live listing yet, so there is no URL to audit. Search language belongs in the keyword surfaces; product differentiation belongs in screenshots, the description body, and promo text.

1. Pick one winnable target keyword before the listing is written: users plausibly search it, competitors exist but are not all dominant incumbents, recent apps show the niche is alive, the app satisfies the searcher's job directly, and the term is not a competitor trademark.
2. Write name, subtitle, and keyword field inside the hard App Store limits below. Do not repeat a word across the three fields, use no spaces after commas in the keyword field, keep one of singular or plural, and front-load the highest-value terms.
3. Plan screenshots outcome first: screenshot 1 sells the result, screenshot 2 sells the differentiator, captions use the searcher's words.
4. Run every claim through a feature-truth check. Never advertise a feature the build does not have.
5. Set a 2 to 4 week measurement plan for rankings, impressions, product page conversion, and promo text or caption rotation.

Hard limits (confirm against the dated Apple reference file before shipping): app name 30 characters, subtitle 30, keyword field 100 (comma-separated), promotional text 170.

Output artifacts:

• aso/keywords.md and aso/aso-doc.md
• fastlane/metadata/<locale>/name.txt, subtitle.txt, keywords.txt, description.txt, and promotional_text.txt
• a screenshot title plan and the ordered screenshot asset list

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Common Issues Checklist

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.

Every flag carries an author action, so the reader knows what to do with it:

Action	Meaning
Blocks the listing	Risks rejection, removal, or ranking suppression. Fix before the next submission.
Required	Costs measurable installs or conversion. Fix in the next release cycle.
Optional	Upside, not a defect. Ship if capacity allows.

Always flag (all tiers):

• Rating below 4.0: required
• Last update > 3 months ago: required
• Google Play description has no keyword strategy (under 1% density): required
• Google Play missing feature graphic: blocks the listing (no featured placement without it)
• Apple keyword field likely has repeated words (inferred from title+subtitle): required
• Category mismatch (app would face less competition in a different category): required
• Fewer than 5 screenshots: required

Flag for Challenger/Established only (not mistakes for Dominant apps):

• Title wastes characters on brand name only (no keywords): required (Dominant: brand IS the keyword)
• Subtitle/short description duplicates title keywords: required
• Description first 3 lines are generic: required (Dominant: may be brand-voice choice)
• No preview video: optional (Dominant: may be rational if product is hard to demo)
• Screenshots are just UI dumps with no messaging/captions: required (Dominant: lifestyle/brand shots may convert better)
• Only 1-2 localizations: optional (score relative to actual market, not absolute count)
• No in-app events or promotional content: optional (Dominant utility apps may not need discovery help)

Flag for all tiers but note context:

• No developer responses to negative reviews: required (note volume: responding at 10M+ reviews is a different challenge than at 1K)
• Generic "What's New" text: optional (Apple 2.3.12 makes it blocks the listing when the release carries significant changes)

Prohibited title metadata (emojis, ALL CAPS, "best"/"#1"/"free", CTAs on Google Play) is always blocks the listing: see references/google-play-specs.md.

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Task-Specific Questions

1. What is the App Store or Google Play URL?
2. Is this your app or a competitor's?
3. What category does the app compete in?
4. Do you have competitor URLs to compare against?
5. Are you focused on search visibility, conversion rate, or both?
6. Do you have access to App Store Connect or Google Play Console data?

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Boundaries

• Do not claim keyword rank, conversion lift, review status, or store approval without a current source or console readback.
• Do not edit or submit store metadata, screenshots, builds, prices, or releases without explicit authorization.
• Do not invent competitor performance, customer sentiment, or platform benchmarks; label estimates and their source dates.
• Do not reuse copyrighted competitor assets or generate an alternate Suede S in screenshot recommendations.

Routing

• Need paid app-install creative -> use suede-ad-creative.
• Need install attribution or in-app events -> use suede-analytics.
• Need customer language for listing copy -> use suede-customer-research.
• Need an iOS or Android product build -> use site-to-ios-app or android-app-factory; native iOS from scratch is a private Suede Labs companion, not in this pack: ios-app-factory.
• Need App Store metadata authored for an app that has not shipped yet -> stay in suede-aso and run Pre-Launch Metadata Mode.
• From those skills, route listing audits, metadata strategy, and screenshot sequencing back to suede-aso.