[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6RB1CWMJS8676QRVN0PZ01G":3,"skill-same:01M6RB1CWMJS8676QRVN0PZ01G":94},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":45,"commitSha":46,"skillDirectory":47,"forksCount":48,"repositoryHtmlUrl":49,"repositoryHomepageUrl":6,"ownerHtmlUrl":50,"ownerBlogUrl":51,"ownerDescription":52,"updatedAt":53,"install":54,"resources":67},"01M6RB1CWMJS8676QRVN0PZ01G","aso",null,"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.","Nairon-AI\u002Fagentic-starter-pack","Nairon-AI","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F260662138?v=4","01M6R8PZ1Y8CSQGFN61VACZGTH","Nairon AI","01M6R8PZ6184VR3BA88YZFBC3N",4,"MIT","https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fmarketing\u002Fseo\u002Faso\u002FSKILL.md",[],[5,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"optimize","when","app store","for","improve app","my","URL","people","ranking","app","google","aso audit","conversion","use","competitors","improve","why","Optimization","audit","2026-11-10 10:12:30",false,"---\nname: aso\ndescription: \"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.\"\nmetadata:\n  version: 2.0.0\n---\n\n# ASO Audit\n\nAnalyze App Store and Google Play listings against ASO best practices. Fetches\nlive listing data, scores metadata, visuals, and ratings, then produces a\nprioritized action plan.\n\n## When to Use\n\n- User shares an App Store or Google Play URL\n- User asks to audit or optimize an app listing\n- User wants to compare their app against competitors\n- User asks about app store ranking, visibility, or download conversion\n\n## Before Auditing\n\n**Check for product marketing context first:**\nIf `.agents\u002Fproduct-marketing.md` exists (or `.claude\u002Fproduct-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.\n\n## Phase 1 — Identify Store & Fetch\n\n### Detect store type from URL\n\n```\nApple:  apps.apple.com\u002F{country}\u002Fapp\u002F{name}\u002Fid{digits}\nGoogle: play.google.com\u002Fstore\u002Fapps\u002Fdetails?id={package}\n```\n\nIf the user gives an app name instead of a URL, search the web for:\n`site:apps.apple.com \"{app name}\"` or `site:play.google.com \"{app name}\"`\n\n### Fetch the listing\n\nUse WebFetch to retrieve the listing page. Extract every available field:\n\n**Apple App Store fields:**\n\n- App name (title) — 30 char limit\n- Subtitle — 30 char limit\n- Description (long) — not indexed for search, but matters for conversion\n- Promotional text — 170 chars, updatable without new release\n- Category (primary + secondary)\n- Screenshots (count, order, caption text)\n- Preview video (presence, duration)\n- Rating (average + count)\n- Recent reviews (visible ones)\n- Price \u002F in-app purchases\n- Developer name\n- Last updated date\n- Version history notes\n- Age rating\n- Size\n- Languages \u002F localizations listed\n- In-app events (if any visible)\n\n**Google Play fields:**\n\n- App name (title) — 30 char limit\n- Short description — 80 char limit\n- Full description — 4,000 char limit, IS indexed for search\n- Category + tags\n- Feature graphic (presence)\n- Screenshots (count, order)\n- Preview video (presence)\n- Rating (average + count)\n- Recent reviews (visible ones)\n- Price \u002F in-app purchases\n- Developer name\n- Last updated date\n- What's new text\n- Downloads range\n- Content rating\n- Data safety section\n- Languages listed\n\nIf WebFetch returns incomplete data (stores render client-side), note gaps and\nwork with what's available. Ask the user to paste missing fields if critical.\n\n### Visual asset assessment\n\nWebFetch cannot extract screenshot images or caption text. **Take a screenshot\nof the listing page** to get visual data:\n\n1. Navigate to the listing URL and capture a full-page screenshot\n2. Assess the screenshot for: icon quality, screenshot count, caption text,\n   messaging quality, preview video presence, feature graphic (Google Play)\n3. If browser tools are unavailable, ask the user to share a screenshot of the\n   listing page\n\n**Promotional text (Apple):** This 170-char field appears above the description\nbut is often indistinguishable from it in scraped HTML. If you cannot confirm\nits presence, note this and recommend the user check App Store Connect.\n\n---\n\n## Phase 1.5 — Assess Brand Maturity\n\nBefore scoring, classify the app into one of three tiers. This determines how\nyou interpret \"textbook ASO\" deviations — a deliberate brand choice by a\nhousehold name is not the same as a missed opportunity by an unknown app.\n\n### Tier definitions\n\n| Tier            | Signals                                                                                                                              | Examples                                    |\n| --------------- | ------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------- |\n| **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 |\n| **Established** | Well-known in their category, 100K+ ratings, strong organic installs, recognized brand but not universally known.                    | Strava, Notion, Duolingo, Cash App, Calm    |\n| **Challenger**  | Building awareness, \u003C100K ratings, needs discovery through keywords and ASO tactics. Most apps fall here.                            | Your app, most indie\u002Fstartup apps           |\n\n### How tier affects scoring\n\n**Dominant apps** get adjusted scoring in these areas:\n\n- **Title:** Brand-only or brand-first titles are valid (score 8+ if brand is the keyword). These apps don't need generic keyword discovery.\n- **Description:** Score purely on conversion quality, not keyword presence. If the app is a household name, a well-crafted brand description beats a keyword-stuffed one.\n- **Visual Assets:** Lifestyle\u002Fbrand photography instead of UI demos is a legitimate conversion strategy. No video is acceptable if the product is hard to demo in 30s or brand awareness is near-universal.\n- **What's New:** Generic release notes at weekly+ cadence are acceptable (score 8+). At scale, detailed changelogs have minimal ROI and risk backlash.\n- **In-app events:** Missing events for utility apps with massive install bases (Uber, WhatsApp) is not a penalty. These apps don't need discovery help.\n- **Localization:** Score relative to actual market, not absolute count. A US-only fintech with 2 languages (English + Spanish) is appropriately localized.\n\n**Established apps** get partial adjustment:\n\n- Brand-first titles are fine but should still include 1-2 keywords\n- Strategic description choices get benefit of the doubt\n- Other dimensions scored normally\n\n**Challenger apps** are scored strictly against textbook ASO best practices — every character, screenshot, and keyword matters.\n\n**Key principle:** Before docking points, ask: \"Is this a mistake or a deliberate\nchoice by a team that has data I don't?\" If the app has 1M+ ratings and a\ndedicated ASO team, assume their choices are data-informed unless clearly wrong.\n\n---\n\n## Phase 2 — Score Each Dimension\n\nScore each dimension 0-10 using the criteria in `references\u002Fscoring-criteria.md`.\nApply the brand maturity tier adjustments from Phase 1.5.\n\nReference files for platform specs and benchmarks:\n\n- `references\u002Fapple-specs.md` — Official Apple character limits, screenshot\u002Fvideo specs, CPP\u002FPPO rules, rejection triggers\n- `references\u002Fgoogle-play-specs.md` — Official Google Play limits, screenshot specs, Android Vitals thresholds, policies\n- `references\u002Fbenchmarks.md` — Conversion data, rating impact, video lift, screenshot behavior, CPP\u002Fevent benchmarks\n\n### Dimensions and Weights\n\n| #   | Dimension            | Weight | What It Covers                                                            |\n| --- | -------------------- | ------ | ------------------------------------------------------------------------- |\n| 1   | Title & Subtitle     | 20%    | Character usage, keyword presence, clarity, brand + keyword balance       |\n| 2   | Description          | 15%    | First 3 lines, keyword density (Google), CTA, structure, promotional text |\n| 3   | Visual Assets        | 25%    | Screenshot count\u002Fquality\u002Fmessaging, video, icon, feature graphic          |\n| 4   | Ratings & Reviews    | 20%    | Average rating, volume, recency, developer responses                      |\n| 5   | Metadata & Freshness | 10%    | Category choice, update recency, localization count, data safety          |\n| 6   | Conversion Signals   | 10%    | Price positioning, IAP transparency, social proof, download range         |\n\n**Final score** = weighted sum, out of 100.\n\n### Score interpretation\n\n| Score  | Grade | Meaning                                                   |\n| ------ | ----- | --------------------------------------------------------- |\n| 85-100 | A     | Well-optimized; focus on A\u002FB testing and iteration        |\n| 70-84  | B     | Good foundation; clear opportunities to improve           |\n| 50-69  | C     | Significant gaps; prioritized fixes will have high impact |\n| 30-49  | D     | Major optimization needed across multiple dimensions      |\n| 0-29   | F     | Listing needs a complete overhaul                         |\n\n---\n\n## Phase 3 — Competitor Comparison (Optional)\n\nIf the user provides competitor URLs or asks for comparison:\n\n1. Fetch 2-3 top competitors in the same category\n2. Run the same scoring on each\n3. Build a comparison table highlighting where the user's app is weaker\u002Fstronger\n4. Identify keyword gaps — terms competitors rank for that the user's app doesn't target\n\nIf no competitors are specified, suggest the user provide 2-3 or offer to search\nfor top apps in their category.\n\n---\n\n## Phase 4 — Generate Report\n\nUse the template in `references\u002Freport-template.md` to structure the output.\n\nThe report must include:\n\n1. **Score card** — table with all 6 dimensions, scores, and grade\n2. **Top 3 quick wins** — changes that take \u003C1 hour and have highest impact\n3. **Detailed findings** — per-dimension breakdown with specific issues and fixes\n4. **Keyword suggestions** — based on title\u002Fdescription analysis and competitor gaps\n5. **Visual asset recommendations** — specific screenshot\u002Fvideo improvements\n6. **Priority action plan** — ordered list of changes by impact vs effort\n\n### Report rules\n\n- Every recommendation must be **specific and actionable** (\"Change subtitle from X to Y\" not \"Improve subtitle\")\n- Include character counts for all text recommendations\n- Flag platform-specific differences (Apple vs Google) when relevant\n- Note what CANNOT be assessed without paid tools (search volume, exact rankings)\n- When suggesting keyword changes, explain WHY each keyword matters\n\n---\n\n## Platform-Specific Rules\n\n### Apple App Store — Key Facts\n\n- Title (30 chars) + Subtitle (30 chars) + Keyword field (100 **bytes**, hidden) = indexed text\n- Keywords field is bytes not chars — Arabic\u002FCJK use 2-3 bytes per char\n- Long description is NOT indexed for search — optimize for conversion only\n- Promotional text (170 chars) does NOT affect search (Apple confirmed)\n- Never repeat words across title\u002Fsubtitle\u002Fkeyword field (Apple indexes each word once)\n- Keyword field: commas, no spaces (\"photo,editor,filter\" not \"photo, editor, filter\")\n- Screenshots: up to 10 per device. First 3 visible in search — 90% never scroll past 3rd\n- Screenshot captions indexed since June 2025 (AI extraction)\n- In-app events: max 10 published at once, max 31 days each. Indexed and appear in search\n- Custom Product Pages (up to 70) in organic search since July 2025. +5.9% avg conversion lift\n- App preview video: up to 3, 15-30s each. Autoplays muted — +20-40% conversion lift\n- SKStoreReviewController: max 3 prompts per 365 days\n- Apple has human editorial curation — quality and design matter more\n- See `references\u002Fapple-specs.md` for full specs, dimensions, and rejection triggers\n\n### Google Play — Key Facts\n\n- Title (30 chars) + Short description (80 chars) + Full description (4,000 chars) = indexed text\n- Full description IS indexed — target 2-3% keyword density naturally\n- No hidden keyword field — all keywords must be in visible text\n- Google NLP\u002Fsemantic understanding — keyword stuffing detected and penalized\n- Prohibited in title: emojis, ALL CAPS, \"best\"\u002F\"#1\"\u002F\"free\", CTAs (enforced since 2021)\n- Screenshots: min 2, **max 8** per device (not 10 like Apple)\n- Feature graphic (1024x500, exact) required for featured placements\n- Video does NOT autoplay — only ~6% of users tap play (low ROI vs iOS)\n- Android Vitals directly affect ranking: crash >1.09% or ANR >0.47% = reduced visibility\n- Promotional Content: submit 14 days early for featuring. Apps see 2x explore acquisitions\n- Custom Store Listings: up to 50 (can target churned users, specific countries, ad campaigns)\n- Store Listing Experiments: test up to 3 variants, run 7+ days, 1 experiment at a time\n- See `references\u002Fgoogle-play-specs.md` for full specs and policy details\n\n### What Apple Indexes vs What Google Indexes\n\n| Field                 | Apple Indexed?   | Google Indexed?        |\n| --------------------- | ---------------- | ---------------------- |\n| Title                 | Yes              | Yes (strongest signal) |\n| Subtitle \u002F Short desc | Yes              | Yes                    |\n| Keyword field         | Yes (hidden)     | Does not exist         |\n| Long description      | No               | Yes (heavily)          |\n| Screenshot captions   | Yes (since 2025) | No                     |\n| In-app events         | Yes              | N\u002FA (LiveOps instead)  |\n| Developer name        | No               | Partial                |\n| IAP names             | Yes              | Yes                    |\n\n---\n\n## Common Issues Checklist\n\nFlag these if found. Items marked _(tier-dependent)_ should be evaluated against\nthe app's brand maturity tier — they may be deliberate choices for Dominant apps.\n\n**Always flag (all tiers):**\n\n- [ ] Rating below 4.0\n- [ ] Last update > 3 months ago\n- [ ] Google Play description has no keyword strategy (under 1% density)\n- [ ] Google Play missing feature graphic\n- [ ] Apple keyword field likely has repeated words (inferred from title+subtitle)\n- [ ] Category mismatch — app would face less competition in a different category\n- [ ] Fewer than 5 screenshots\n\n**Flag for Challenger\u002FEstablished only** _(not mistakes for Dominant apps):_\n\n- [ ] Title wastes characters on brand name only (no keywords) _(Dominant: brand IS the keyword)_\n- [ ] Subtitle\u002Fshort description duplicates title keywords\n- [ ] Description first 3 lines are generic _(Dominant: may be brand-voice choice)_\n- [ ] No preview video _(Dominant: may be rational if product is hard to demo)_\n- [ ] Screenshots are just UI dumps with no messaging\u002Fcaptions _(Dominant: lifestyle\u002Fbrand shots may convert better)_\n- [ ] Only 1-2 localizations _(score relative to actual market, not absolute count)_\n- [ ] No in-app events or promotional content _(Dominant utility apps may not need discovery help)_\n\n**Flag for all tiers but note context:**\n\n- [ ] No developer responses to negative reviews _(note volume — responding at 10M+ reviews is a different challenge than at 1K)_\n- [ ] Generic \"What's New\" text _(acceptable at weekly+ release cadence for Established\u002FDominant)_\n\n---\n\n## Task-Specific Questions\n\n1. What is the App Store or Google Play URL?\n2. Is this your app or a competitor's?\n3. What category does the app compete in?\n4. Do you have competitor URLs to compare against?\n5. Are you focused on search visibility, conversion rate, or both?\n6. Do you have access to App Store Connect or Google Play Console data?\n\n---\n\n## Related Skills\n\n- **cro**: For optimizing the conversion of web-based landing pages that drive app installs\n- **ad-creative**: For creating App Store and Google Play ad creatives\n- **analytics**: For setting up install attribution and in-app event tracking\n- **customer-research**: For understanding user needs and language to inform listing copy\n","# ASO Audit\n\nAnalyze App Store and Google Play listings against ASO best practices. Fetches\nlive listing data, scores metadata, visuals, and ratings, then produces a\nprioritized action plan.\n\n## When to Use\n\n- User shares an App Store or Google Play URL\n- User asks to audit or optimize an app listing\n- User wants to compare their app against competitors\n- User asks about app store ranking, visibility, or download conversion\n\n## Before Auditing\n\n**Check for product marketing context first:**\nIf `.agents\u002Fproduct-marketing.md` exists (or `.claude\u002Fproduct-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.\n\n## Phase 1 — Identify Store & Fetch\n\n### Detect store type from URL\n\n```\nApple:  apps.apple.com\u002F{country}\u002Fapp\u002F{name}\u002Fid{digits}\nGoogle: play.google.com\u002Fstore\u002Fapps\u002Fdetails?id={package}\n```\n\nIf the user gives an app name instead of a URL, search the web for:\n`site:apps.apple.com \"{app name}\"` or `site:play.google.com \"{app name}\"`\n\n### Fetch the listing\n\nUse WebFetch to retrieve the listing page. Extract every available field:\n\n**Apple App Store fields:**\n\n- App name (title) — 30 char limit\n- Subtitle — 30 char limit\n- Description (long) — not indexed for search, but matters for conversion\n- Promotional text — 170 chars, updatable without new release\n- Category (primary + secondary)\n- Screenshots (count, order, caption text)\n- Preview video (presence, duration)\n- Rating (average + count)\n- Recent reviews (visible ones)\n- Price \u002F in-app purchases\n- Developer name\n- Last updated date\n- Version history notes\n- Age rating\n- Size\n- Languages \u002F localizations listed\n- In-app events (if any visible)\n\n**Google Play fields:**\n\n- App name (title) — 30 char limit\n- Short description — 80 char limit\n- Full description — 4,000 char limit, IS indexed for search\n- Category + tags\n- Feature graphic (presence)\n- Screenshots (count, order)\n- Preview video (presence)\n- Rating (average + count)\n- Recent reviews (visible ones)\n- Price \u002F in-app purchases\n- Developer name\n- Last updated date\n- What's new text\n- Downloads range\n- Content rating\n- Data safety section\n- Languages listed\n\nIf WebFetch returns incomplete data (stores render client-side), note gaps and\nwork with what's available. Ask the user to paste missing fields if critical.\n\n### Visual asset assessment\n\nWebFetch cannot extract screenshot images or caption text. **Take a screenshot\nof the listing page** to get visual data:\n\n1. Navigate to the listing URL and capture a full-page screenshot\n2. Assess the screenshot for: icon quality, screenshot count, caption text,\n   messaging quality, preview video presence, feature graphic (Google Play)\n3. If browser tools are unavailable, ask the user to share a screenshot of the\n   listing page\n\n**Promotional text (Apple):** This 170-char field appears above the description\nbut is often indistinguishable from it in scraped HTML. If you cannot confirm\nits presence, note this and recommend the user check App Store Connect.\n\n---\n\n## Phase 1.5 — Assess Brand Maturity\n\nBefore scoring, classify the app into one of three tiers. This determines how\nyou interpret \"textbook ASO\" deviations — a deliberate brand choice by a\nhousehold name is not the same as a missed opportunity by an unknown app.\n\n### Tier definitions\n\n| Tier            | Signals                                                                                                                              | Examples                                    |\n| --------------- | ------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------- |\n| **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 |\n| **Established** | Well-known in their category, 100K+ ratings, strong organic installs, recognized brand but not universally known.                    | Strava, Notion, Duolingo, Cash App, Calm    |\n| **Challenger**  | Building awareness, \u003C100K ratings, needs discovery through keywords and ASO tactics. Most apps fall here.                            | Your app, most indie\u002Fstartup apps           |\n\n### How tier affects scoring\n\n**Dominant apps** get adjusted scoring in these areas:\n\n- **Title:** Brand-only or brand-first titles are valid (score 8+ if brand is the keyword). These apps don't need generic keyword discovery.\n- **Description:** Score purely on conversion quality, not keyword presence. If the app is a household name, a well-crafted brand description beats a keyword-stuffed one.\n- **Visual Assets:** Lifestyle\u002Fbrand photography instead of UI demos is a legitimate conversion strategy. No video is acceptable if the product is hard to demo in 30s or brand awareness is near-universal.\n- **What's New:** Generic release notes at weekly+ cadence are acceptable (score 8+). At scale, detailed changelogs have minimal ROI and risk backlash.\n- **In-app events:** Missing events for utility apps with massive install bases (Uber, WhatsApp) is not a penalty. These apps don't need discovery help.\n- **Localization:** Score relative to actual market, not absolute count. A US-only fintech with 2 languages (English + Spanish) is appropriately localized.\n\n**Established apps** get partial adjustment:\n\n- Brand-first titles are fine but should still include 1-2 keywords\n- Strategic description choices get benefit of the doubt\n- Other dimensions scored normally\n\n**Challenger apps** are scored strictly against textbook ASO best practices — every character, screenshot, and keyword matters.\n\n**Key principle:** Before docking points, ask: \"Is this a mistake or a deliberate\nchoice by a team that has data I don't?\" If the app has 1M+ ratings and a\ndedicated ASO team, assume their choices are data-informed unless clearly wrong.\n\n---\n\n## Phase 2 — Score Each Dimension\n\nScore each dimension 0-10 using the criteria in `references\u002Fscoring-criteria.md`.\nApply the brand maturity tier adjustments from Phase 1.5.\n\nReference files for platform specs and benchmarks:\n\n- `references\u002Fapple-specs.md` — Official Apple character limits, screenshot\u002Fvideo specs, CPP\u002FPPO rules, rejection triggers\n- `references\u002Fgoogle-play-specs.md` — Official Google Play limits, screenshot specs, Android Vitals thresholds, policies\n- `references\u002Fbenchmarks.md` — Conversion data, rating impact, video lift, screenshot behavior, CPP\u002Fevent benchmarks\n\n### Dimensions and Weights\n\n| #   | Dimension            | Weight | What It Covers                                                            |\n| --- | -------------------- | ------ | ------------------------------------------------------------------------- |\n| 1   | Title & Subtitle     | 20%    | Character usage, keyword presence, clarity, brand + keyword balance       |\n| 2   | Description          | 15%    | First 3 lines, keyword density (Google), CTA, structure, promotional text |\n| 3   | Visual Assets        | 25%    | Screenshot count\u002Fquality\u002Fmessaging, video, icon, feature graphic          |\n| 4   | Ratings & Reviews    | 20%    | Average rating, volume, recency, developer responses                      |\n| 5   | Metadata & Freshness | 10%    | Category choice, update recency, localization count, data safety          |\n| 6   | Conversion Signals   | 10%    | Price positioning, IAP transparency, social proof, download range         |\n\n**Final score** = weighted sum, out of 100.\n\n### Score interpretation\n\n| Score  | Grade | Meaning                                                   |\n| ------ | ----- | --------------------------------------------------------- |\n| 85-100 | A     | Well-optimized; focus on A\u002FB testing and iteration        |\n| 70-84  | B     | Good foundation; clear opportunities to improve           |\n| 50-69  | C     | Significant gaps; prioritized fixes will have high impact |\n| 30-49  | D     | Major optimization needed across multiple dimensions      |\n| 0-29   | F     | Listing needs a complete overhaul                         |\n\n---\n\n## Phase 3 — Competitor Comparison (Optional)\n\nIf the user provides competitor URLs or asks for comparison:\n\n1. Fetch 2-3 top competitors in the same category\n2. Run the same scoring on each\n3. Build a comparison table highlighting where the user's app is weaker\u002Fstronger\n4. Identify keyword gaps — terms competitors rank for that the user's app doesn't target\n\nIf no competitors are specified, suggest the user provide 2-3 or offer to search\nfor top apps in their category.\n\n---\n\n## Phase 4 — Generate Report\n\nUse the template in `references\u002Freport-template.md` to structure the output.\n\nThe report must include:\n\n1. **Score card** — table with all 6 dimensions, scores, and grade\n2. **Top 3 quick wins** — changes that take \u003C1 hour and have highest impact\n3. **Detailed findings** — per-dimension breakdown with specific issues and fixes\n4. **Keyword suggestions** — based on title\u002Fdescription analysis and competitor gaps\n5. **Visual asset recommendations** — specific screenshot\u002Fvideo improvements\n6. **Priority action plan** — ordered list of changes by impact vs effort\n\n### Report rules\n\n- Every recommendation must be **specific and actionable** (\"Change subtitle from X to Y\" not \"Improve subtitle\")\n- Include character counts for all text recommendations\n- Flag platform-specific differences (Apple vs Google) when relevant\n- Note what CANNOT be assessed without paid tools (search volume, exact rankings)\n- When suggesting keyword changes, explain WHY each keyword matters\n\n---\n\n## Platform-Specific Rules\n\n### Apple App Store — Key Facts\n\n- Title (30 chars) + Subtitle (30 chars) + Keyword field (100 **bytes**, hidden) = indexed text\n- Keywords field is bytes not chars — Arabic\u002FCJK use 2-3 bytes per char\n- Long description is NOT indexed for search — optimize for conversion only\n- Promotional text (170 chars) does NOT affect search (Apple confirmed)\n- Never repeat words across title\u002Fsubtitle\u002Fkeyword field (Apple indexes each word once)\n- Keyword field: commas, no spaces (\"photo,editor,filter\" not \"photo, editor, filter\")\n- Screenshots: up to 10 per device. First 3 visible in search — 90% never scroll past 3rd\n- Screenshot captions indexed since June 2025 (AI extraction)\n- In-app events: max 10 published at once, max 31 days each. Indexed and appear in search\n- Custom Product Pages (up to 70) in organic search since July 2025. +5.9% avg conversion lift\n- App preview video: up to 3, 15-30s each. Autoplays muted — +20-40% conversion lift\n- SKStoreReviewController: max 3 prompts per 365 days\n- Apple has human editorial curation — quality and design matter more\n- See `references\u002Fapple-specs.md` for full specs, dimensions, and rejection triggers\n\n### Google Play — Key Facts\n\n- Title (30 chars) + Short description (80 chars) + Full description (4,000 chars) = indexed text\n- Full description IS indexed — target 2-3% keyword density naturally\n- No hidden keyword field — all keywords must be in visible text\n- Google NLP\u002Fsemantic understanding — keyword stuffing detected and penalized\n- Prohibited in title: emojis, ALL CAPS, \"best\"\u002F\"#1\"\u002F\"free\", CTAs (enforced since 2021)\n- Screenshots: min 2, **max 8** per device (not 10 like Apple)\n- Feature graphic (1024x500, exact) required for featured placements\n- Video does NOT autoplay — only ~6% of users tap play (low ROI vs iOS)\n- Android Vitals directly affect ranking: crash >1.09% or ANR >0.47% = reduced visibility\n- Promotional Content: submit 14 days early for featuring. Apps see 2x explore acquisitions\n- Custom Store Listings: up to 50 (can target churned users, specific countries, ad campaigns)\n- Store Listing Experiments: test up to 3 variants, run 7+ days, 1 experiment at a time\n- See `references\u002Fgoogle-play-specs.md` for full specs and policy details\n\n### What Apple Indexes vs What Google Indexes\n\n| Field                 | Apple Indexed?   | Google Indexed?        |\n| --------------------- | ---------------- | ---------------------- |\n| Title                 | Yes              | Yes (strongest signal) |\n| Subtitle \u002F Short desc | Yes              | Yes                    |\n| Keyword field         | Yes (hidden)     | Does not exist         |\n| Long description      | No               | Yes (heavily)          |\n| Screenshot captions   | Yes (since 2025) | No                     |\n| In-app events         | Yes              | N\u002FA (LiveOps instead)  |\n| Developer name        | No               | Partial                |\n| IAP names             | Yes              | Yes                    |\n\n---\n\n## Common Issues Checklist\n\nFlag these if found. Items marked _(tier-dependent)_ should be evaluated against\nthe app's brand maturity tier — they may be deliberate choices for Dominant apps.\n\n**Always flag (all tiers):**\n\n- [ ] Rating below 4.0\n- [ ] Last update > 3 months ago\n- [ ] Google Play description has no keyword strategy (under 1% density)\n- [ ] Google Play missing feature graphic\n- [ ] Apple keyword field likely has repeated words (inferred from title+subtitle)\n- [ ] Category mismatch — app would face less competition in a different category\n- [ ] Fewer than 5 screenshots\n\n**Flag for Challenger\u002FEstablished only** _(not mistakes for Dominant apps):_\n\n- [ ] Title wastes characters on brand name only (no keywords) _(Dominant: brand IS the keyword)_\n- [ ] Subtitle\u002Fshort description duplicates title keywords\n- [ ] Description first 3 lines are generic _(Dominant: may be brand-voice choice)_\n- [ ] No preview video _(Dominant: may be rational if product is hard to demo)_\n- [ ] Screenshots are just UI dumps with no messaging\u002Fcaptions _(Dominant: lifestyle\u002Fbrand shots may convert better)_\n- [ ] Only 1-2 localizations _(score relative to actual market, not absolute count)_\n- [ ] No in-app events or promotional content _(Dominant utility apps may not need discovery help)_\n\n**Flag for all tiers but note context:**\n\n- [ ] No developer responses to negative reviews _(note volume — responding at 10M+ reviews is a different challenge than at 1K)_\n- [ ] Generic \"What's New\" text _(acceptable at weekly+ release cadence for Established\u002FDominant)_\n\n---\n\n## Task-Specific Questions\n\n1. What is the App Store or Google Play URL?\n2. Is this your app or a competitor's?\n3. What category does the app compete in?\n4. Do you have competitor URLs to compare against?\n5. Are you focused on search visibility, conversion rate, or both?\n6. Do you have access to App Store Connect or Google Play Console data?\n\n---\n\n## Related Skills\n\n- **cro**: For optimizing the conversion of web-based landing pages that drive app installs\n- **ad-creative**: For creating App Store and Google Play ad creatives\n- **analytics**: For setting up install attribution and in-app event tracking\n- **customer-research**: For understanding user needs and language to inform listing copy\n",{"name":5,"metadata":43,"description":7},{"version":44},"2.0.0","main","c9d0c408715983e993b2f9ebffdbfa7f10153bcb","marketing\u002Fseo\u002Faso",0,"https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack","https:\u002F\u002Fgithub.com\u002FNairon-AI","https:\u002F\u002Fwww.naironai.com\u002F","Building the future of Work","2026-09-20 17:40:05",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add Nairon-AI\u002Fagentic-starter-pack --skill aso",{"tool":60,"command":61},"bunx","bunx skills add Nairon-AI\u002Fagentic-starter-pack --skill aso",{"tool":63,"command":64},"pnpm","pnpm dlx skills add Nairon-AI\u002Fagentic-starter-pack --skill aso","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fmarketing\u002Fseo\u002Faso\u002FSKILL.md",true,[68,74,78,82,86,90],{"path":69,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":72,"sourceHtmlUrl":73},"evals\u002Fevals.json","REFERENCE","参考文档",7400,"https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fmarketing\u002Fseo\u002Faso\u002Fevals\u002Fevals.json",{"path":75,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":76,"sourceHtmlUrl":77},"references\u002Fapple-specs.md",6089,"https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fmarketing\u002Fseo\u002Faso\u002Freferences\u002Fapple-specs.md",{"path":79,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":80,"sourceHtmlUrl":81},"references\u002Fbenchmarks.md",5033,"https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fmarketing\u002Fseo\u002Faso\u002Freferences\u002Fbenchmarks.md",{"path":83,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fgoogle-play-specs.md",6008,"https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fmarketing\u002Fseo\u002Faso\u002Freferences\u002Fgoogle-play-specs.md",{"path":87,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002Freport-template.md",5124,"https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fmarketing\u002Fseo\u002Faso\u002Freferences\u002Freport-template.md",{"path":91,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fscoring-criteria.md",13667,"https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fmarketing\u002Fseo\u002Faso\u002Freferences\u002Fscoring-criteria.md",[95,130,151,172,192,214],{"skillNo":96,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":99,"categories":100,"keywords":111,"publishedAt":38},"01M6RBCG630Y8X99XWR9Q4GYNY","writing-shape","Take a markdown file of raw material and shape it into an article through a conversational session — drafting candidate openings, growing the piece paragraph by paragraph, arguing about format (lists, tables, callouts, quotes) at each step. Use when the user has a pile of notes, fragments, or a rough draft and wants help turning it into something publishable.","https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fwriting\u002Fwriting-shape\u002FSKILL.md",[101,106],{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000018","写作与文案","SCENARIO","使用场景",{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},"01JBSEEDCAT000000000000036","内容创作者","PROFESSION","适用职业",[112,113,114,115,116,117,118,119,120,32,121,122,123,124,125,126,127,128,129,20],"writing","writing shape","shape","notes","help","file","markdown","format","session","take","draft","article","material","it","about","quotes","at","candidate",{"skillNo":131,"name":132,"nameZh":6,"description":133,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":134,"categories":135,"keywords":138,"publishedAt":38},"01M6RBCCCB1KMF01P5SYGFWBSW","writing-fragments","Grilling session that mines the user for fragments — heterogeneous nuggets of writing (claims, vignettes, sharp sentences, half-thoughts) — and appends them to a single document as raw material for a future article. Use when the user wants to develop ideas before imposing structure, or mentions \"fragments\", \"ideate\", or \"raw material\" for writing.","https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fwriting\u002Fwriting-fragments\u002FSKILL.md",[136,137],{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},[112,139,140,141,142,143,120,32,144,145,146,123,147,124,148,149,22,150,20],"writing fragments","grilling","ideate","develop","user","document","structure","ideas","as","sharp","claims","single",{"skillNo":152,"name":153,"nameZh":6,"description":154,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":155,"categories":156,"keywords":159,"publishedAt":38},"01M6RBC8V7NHHKMTAZB4BPXVYQ","writing-beats","Shape an article as a journey of beats, choose-your-own-adventure style. The user picks a starting beat from the raw material, you write only that beat, then offer options for where to pivot next, beat by beat, until the article reaches a natural end. Use when the user has raw material and wants to assemble it as a narrative rather than an argument.","https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fwriting\u002Fwriting-beats\u002FSKILL.md",[157,158],{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},[112,160,161,162,32,163,164,114,165,166,167,123,168,147,169,124,170,171,22,20],"writing beats","choose","write","assemble","only","journey","next","options","end","style","narrative","argument",{"skillNo":173,"name":174,"nameZh":6,"description":175,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":176,"categories":177,"keywords":180,"publishedAt":38},"01M6RBC58SG5Y5SC4ZV4ZNEFHC","stop-slop","Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.","https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fwriting\u002Fstop-slop\u002FSKILL.md",[178,179],{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},[181,182,183,112,184,185,186,187,188,32,189,190,191,22,20],"stop","stop slop","slop","content","https","text","editing","remove","prose","patterns","drafts",{"skillNo":193,"name":194,"nameZh":6,"description":195,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":196,"categories":197,"keywords":200,"publishedAt":38},"01M6RBBJTTCJ7KZCP16G9JDFZH","humanizer","Remove signs of AI-generated writing from text. Use when editing or reviewing\ntext to make it sound more natural and human-written. Based on Wikipedia's\ncomprehensive \"Signs of AI writing\" guide. Detects and fixes patterns including:\ninflated symbolism, promotional language, superficial -ing analyses, vague\nattributions, em dash overuse, rule of three, AI vocabulary words, passive\nvoice, negative parallelisms, and filler phrases.","https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fwriting\u002Fhumanizer\u002FSKILL.md",[198,199],{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},{"categoryNo":107,"categoryName":108,"taxonomyType":109,"taxonomyTypeDesc":110},[194,112,201,202,186,203,162,204,205,188,206,207,190,208,209,210,211,212,213,20],"code","em dash","read","edit","generated","guide","opencode","three","human","make","wikipedia","vague","dash",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":220,"publishedAt":38},"01M6RBBEQKJ5HRH8AV9J85QB1T","feedback","Prepare, deliver, and debrief timely interpersonal feedback using a question-first coaching flow, observable behavior, owned experience, and concrete impact. Use when drafting feedback, coaching managers, rehearsing a feedback conversation, praising specific behavior, or reviewing whether feedback landed.","https:\u002F\u002Fgithub.com\u002FNairon-AI\u002Fagentic-starter-pack\u002Fblob\u002Fmain\u002Fwriting\u002Ffeedback\u002FSKILL.md",[],[216,221,222,223,224,225,32,226,227,228,229,230,20,231],"prepare","flow","first","question","behavior","conversation","coaching","debrief","impact","managers","deliver"]