Best fit
- User shares an App Store or Google Play URL
- User asks to audit or optimize an app listing
- User wants to compare their app against competitors
coreyhaines31/marketingskills
When the user wants to audit or optimize an App Store or Google Play listing. Also use when the user mentions 'ASO audit,' 'app store optimization,' 'optimize my app listing,' 'improve app visibility,' 'app store ranking,' 'audit my listing,' 'why aren't people downloading my app,' 'improve my app conversion,' 'keyword optimization for app,' or 'compare my app to competitors.' Use when the user shares an App Store or Google Play URL and wants to improve it.
npx skills add https://github.com/coreyhaines31/marketingskills --skill "skills/aso"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
Analyze App Store and Google Play listings against ASO best practices. Fetches live listing data, scores metadata, visuals, and ratings, then produces a prioritized action plan.
npx skills add https://github.com/coreyhaines31/marketingskills --skill "skills/aso"The pinned source contains enough sections and task detail for a source-grounded deep guide; automated content is still not an independent test.
1,943 source words · 22 usable sections
Best fit
Evidence and findings
Review workflow
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
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}"
WebFetch cannot extract screenshot images or caption text. Take a screenshot of the listing page to get visual data:
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.
Score each dimension 0-10 using the criteria in references/scoring-criteria.md. Apply the brand maturity tier adjustments from Phase 1.5.
If the user provides competitor URLs or asks for comparison:
SkillSignal prompt templates
These prompts were written by SkillSignal from the source structure; they are not upstream text.
Source-grounded prompt
Use for a review or audit task while explicitly checking the source sections.
Use aso for this review or audit task: [task]. Inputs and constraints: [details]. Work through these pinned SKILL.md sections: “Phase 1 — Identify Store & Fetch”, “Visual asset assessment”, “Phase 1.5 — Assess Brand Maturity”, “Phase 2 — Score Each Dimension”, “Phase 3 — Competitor Comparison (Optional)”. Cite the concrete requirements that shape each step, do not invent capabilities absent from the source, and verify the result against: [acceptance criteria].
Review checklist
The source section “Phase 1 — Identify Store & Fetch” has been checked.
The source section “Visual asset assessment” has been checked.
The source section “Phase 1.5 — Assess Brand Maturity” has been checked.
The source section “Phase 2 — Score Each Dimension” has been checked.
Source output checked: Score card — table with all 6 dimensions, scores, and grade
Source output checked: Top 3 quick wins — changes that take <1 hour and have highest impact
Static permission evidence
These are source excerpts matched by deterministic rules, not findings of malicious behavior, safety, or actual execution.
Choose a different workflow
When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps.' Use this for any document or asset that helps a sales team close deals. Fo
A separate implementation from coreyhaines31/marketingskills; compare its source, maintenance signals, and permission requirements.
Open source detailCreate professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.
A separate implementation from K-Dense-AI/scientific-agent-skills; compare its source, maintenance signals, and permission requirements.
Open source detailOptimizes multi-step conversion flows including signup, onboarding, upgrade, and checkout. Maps each step, identifies friction and drop-off risks, then recommends specific copy/UX changes with A/B test plans. Use when someone says 'signup flow', 'onboarding optimization', 'checkout conversion', 'paywall optimization', 'activation rate', 'funnel analysis', 'why are users dropping off', 'registration flow', 'trial conversion', 'free to paid', 'upgrade flow', 'user journey', or wants to improve any
A separate implementation from MoizIbnYousaf/marketing-cli; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
Analyze App Store and Google Play listings against ASO best practices. Fetches live listing data, scores metadata, visuals, and ratings, then produces a prioritized action plan.
The source record exposes this install command: npx skills add https://github.com/coreyhaines31/marketingskills --skill "skills/aso". Inspect the command and pinned source before running it.
Static rules flagged network in the source; the page lists the matching lines and excerpts.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps.' Use this for any document or asset that helps a sales team close deals. Fo
Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.
Optimizes multi-step conversion flows including signup, onboarding, upgrade, and checkout. Maps each step, identifies friction and drop-off risks, then recommends specific copy/UX changes with A/B test plans. Use when someone says 'signup flow', 'onboarding optimization', 'checkout conversion', 'paywall optimization', 'activation rate', 'funnel analysis', 'why are users dropping off', 'registration flow', 'trial conversion', 'free to paid', 'upgrade flow', 'user journey', or wants to improve any
One-click contribution flow for Open Design (nexu-io/open-design) — even for non-coders. Pick one of four cards (ship a Skill or Design System you made with OD; translate docs; fix a typo / write a blog; report a bug), the agent validates and opens a PR (or issue) for you. Trigger words contribute to open design, ship my OD skill, ship my OD design system, translate OD docs, report an OD bug, od-contribute.
When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just
Analyze App Store and Google Play listings against ASO best practices. Fetches live listing data, scores metadata, visuals, and ratings, then produces 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:
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: