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Agent Skill · 研究检索

app-marketing-copy(应用营销文案)

app-marketing-copy 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

app-marketing-copy 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 46,181。

总安装 799周安装 32GitHub Stars 5下载 259核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:app-marketing-copy(应用营销文案)
来源仓库:https://github.com/ckorhonen/claude-skills
仓库路径:skills/app-marketing-copy
安装命令:
npx skills add https://github.com/ckorhonen/claude-skills --skill app-marketing-copy
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ckorhonen/claude-skills --skill app-marketing-copy

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

app-marketing-copy 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 核验具体用法。

安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。当前功能聚焦于生成应用商店文案,包括标题、描述、截图说明和广告素材。

来源仓库内路径:skills/app-marketing-copy

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/ckorhonen/claude-skills --skill app-marketing-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

app-marketing-copy 怎么安装?

在终端执行 npx skills add https://github.com/ckorhonen/claude-skills --skill app-marketing-copy。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

app-marketing-copy 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

app-marketing-copy 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

app-marketing-copy 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

app-marketing-copy 用的人多吗?

公开数据是累计安装 799 次,近一周安装 32 次,下载 259 次,GitHub 5 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

app-marketing-copy 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
app-marketing-copy

应用营销文案 · 本页

7995只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

App Marketing Copy

Quick start

  1. Ask for missing inputs (or infer from repo/product docs):
  • App name + 1-sentence value prop
  • Target user + primary job-to-be-done
  • 3–7 key features + 1–3 differentiators
  • Desired tone (and words to use/avoid)
  • Platform(s): iOS App Store, Google Play, or both
  • Screenshot count and theme (if needed)
  1. Confirm deliverables:
  • Store listing (iOS, Google Play)
  • Marketing pack (landing hero, feature blurbs, CTAs, ads)
  • Screenshot pack (caption copy + image-generation prompts)
  1. Produce 2–3 variants per high-impact field, then recommend a "best pick" with 1-sentence rationale.

Examples

Example 1: New App Store Listing

User input:

App: FocusTimer
Purpose: Pomodoro timer for students
Key features: Custom intervals, study stats, break reminders
Platform: iOS App Store
Tone: Friendly but not childish

Workflow:

  1. Run intake questions to clarify missing details
  2. Generate 3 subtitle variants, recommend best
  3. Create keyword set optimized for student productivity searches
  4. Write full description with feature bullets
  5. Generate 5 screenshot captions in narrative order
  6. Validate with scripts/check_app_store_limits.py

Expected output:

  • iOS App Store listing (all fields within limits)
  • 3 subtitle options with rationale
  • Keyword set (100 chars max)
  • Screenshot copy pack

Example 2: Marketing Copy Refresh

User input:

"Our app store listing conversion is terrible. Help refresh it."
App: PhotoFix (photo editing)
Current problem: Generic copy, keyword-stuffed

Workflow:

  1. Review current listing (if provided)
  2. Ask: "What makes PhotoFix different from competitors?"
  3. Identify ASO keyword stuffing issues
  4. Generate 3 new subtitle variants (specific, benefit-focused)
  5. Rewrite full description with user benefits (not tech specs)
  6. Create fresh screenshot captions
  7. Compare before/after character counts

Expected output:

  • Refactored listing with specificity
  • Side-by-side comparison showing improvements
  • Rationale for each change

Example 3: Multi-Platform Launch

User input:

Launching on both iOS and Google Play
App: TaskFlow (project management for freelancers)
Need everything: store listings, landing page copy, ads

Workflow:

  1. Complete intake (audience, differentiators, proof points)
  2. Generate iOS listing (subtitle, keywords, description)
  3. Generate Google Play listing (short desc, feature bullets, full desc)
  4. Create marketing pack (10 taglines, 3 hero sections, 6 feature blurbs, 10 CTAs)
  5. Generate screenshot copy pack (8 captions + image prompts)
  6. Validate all with scripts/check_app_store_limits.py

Expected output:

  • Complete iOS App Store listing
  • Complete Google Play listing
  • Marketing copy pack (50+ deliverables)
  • Screenshot pack with narrative arc

Intake template (ask, then proceed)

  • Audience: who + what they want
  • Problem: what's hard today
  • Outcome: what "success" looks like
  • Differentiators: why this vs alternatives
  • Proof: numbers, reviews, awards, press (if any)
  • Constraints: claims to avoid, legal/compliance notes, pricing mention policy
  • Locale(s): default to US English unless told otherwise

Outputs

iOS App Store listing

  • Provide: App Name options, Subtitle options, Promotional Text, Keyword set, Full Description, "What's New" (release notes).
  • Enforce field limits; if unsure, open references/app-store-metadata.md or run scripts/check_app_store_limits.py.

Google Play listing

  • Provide: Title options, Short Description options, Full Description, Feature bullets, Release notes.
  • Enforce limits; see references/app-store-metadata.md or scripts/check_app_store_limits.py.

Marketing copy pack

  • Provide: 5-10 taglines, 3 hero sections (headline + subhead + CTA), 6 feature blurbs (1-2 sentences), 10 micro-CTAs, 10 ad hooks (short), 5 social posts.
  • Keep claims supportable; avoid "#1 / best" unless proven.

Screenshot pack (copy + prompts)

  • Provide: 5-8 screenshot captions (2-5 words each) + optional sub-captions; include a narrative order (setup → value → proof → CTA).
  • Provide: per-screenshot art direction + a prompt template for text-to-image generation (backgrounds/illustrations), tailored to the user's tool.
  • Use references/screenshot-prompts.md for prompt patterns and negative prompts.

Quality checks (do before final)

  • Character limits: validate with scripts/check_app_store_limits.py --platform ios --input draft.json (or --platform google_play) for store fields.
  • Consistency: keep the same core value prop across title/subtitle/hero/screenshot 1.
  • Compliance: avoid disallowed claims, competitor trademarks, and sensitive targeting; ask if regulated domain (health/finance/kids).
  • Readability: short sentences, active voice, scannable bullets.

Common Pitfalls

1. ASO Keyword Stuffing (Unnatural, Hurts Conversion)

Problem: Cramming keywords into titles, subtitles, and descriptions makes copy sound robotic and kills conversion rates. App Store algorithms punish overloaded keyword copy in user engagement metrics.

❌ Bad Example (iOS Subtitle):

Photo Editor Photo Filter Photo Effects Photo Editor App

✅ Good Example (iOS Subtitle):

Professional photo editing

Why it fails:

  • The bad version repeats "Photo" 4× and "Editor" 2×, signaling spam to both algorithms and users
  • Reads unnaturally; users abandon apps that feel compromised
  • App Store gives lower ranking boost to keyword-stuffed copy vs. naturally keyword-integrated copy

What to do instead:

  • Each keyword appears once naturally in context
  • Prioritize readability and user benefit over keyword density
  • Let keywords live in distinct fields (keyword set, full description) where they don't disrupt the narrative
  • Example that works: "Photo Editor-Professional Effects, Simplified" (keywords: photo editor, effects; reads naturally)

2. Generic Value Props (Could Apply to Any App)

Problem: Vague promises like "Fast," "Easy," "Simple," or "Best" don't differentiate and raise user skepticism. Without specificity, users can't judge if the app solves *their* problem.

❌ Bad Examples:

- "The easiest way to edit photos"
- "Powerful and intuitive design tool"
- "Professional-grade app for everyone"
- "The best photo editor on the market"

✅ Good Examples (Specific):

- "One-click background removal-no manual selection needed"
- "AI-powered portrait retouching in 3 taps"
- "Batch edit 100 photos with one template"
- "Remove objects from photos—no expensive subscriptions needed"

Why it matters:

  • Generic language applies to 50+ competitors; users skip it
  • Specific claims signal you understand their workflow
  • Specificity = trustworthiness; vague = greenwashing

What to do instead:

  • Lead with outcome + mechanism: "Auto-remove backgrounds in 2 seconds" (not "fast")
  • Show the job-to-be-done: "Batch edit 100 photos" (not "powerful")
  • Contrast against status quo: "No $20/month subscription" (not "affordable")
  • Name the user workflow: "Retouch headshots for LinkedIn" (not "professional")

3. Store Listing Length Violations (Truncated on Store Pages)

Problem: Copy that exceeds field limits gets truncated mid-sentence, breaking the message and confusing users. Different platforms truncate at different character counts, and mobile displays show fewer characters than desktop.

Platform Limits (Enforce Strictly):

FieldiOSGoogle PlayMobile Display
Subtitle30 charsN/A✂️ Truncates at 30 on all devices
Short DescriptionN/A80 chars✂️ Truncates at 50 on mobile
Feature BulletsN/A80 chars each✂️ Truncates at 50 on mobile
Promotional Text170 charsN/A✂️ Truncates at 85 on mobile

❌ Bad Example (iOS Subtitle - 42 chars, exceeds 30-char limit):

Professional photo editing, now simplified

Displays as: "Professional photo editing, now si..." (truncated mid-word)

✅ Good Example (iOS Subtitle - 26 chars, fits perfectly):

Professional photo editing

❌ Bad Example (Google Play Feature Bullet - 93 chars, exceeds 80-char limit):

Automatically remove backgrounds from any photo without manual selection or complicated tools

Displays as: "Automatically remove backgrounds from any photo without manual selection or..." (incomplete thought)

✅ Good Example (Google Play Feature Bullet - 61 chars, fits with room):

Auto-remove backgrounds in seconds—no manual selection needed

What to do instead:

  • Always run copy through scripts/check_app_store_limits.py before final
  • Write tight; avoid filler words (a, the, very, really, just)
  • Prioritize the first 50 characters-everything after may be hidden on mobile
  • Use contractions (don't, it's) to save characters without losing personality

4. Feature Bullets as Technical Specs (Not User Benefits)

Problem: Listing technical features instead of outcomes confuses users about what they can *do* with the app. Users don't buy specs; they buy results.

❌ Bad Examples (Technical Specs):

- Advanced color grading engine with 256-bit processing
- Support for RAW file formats (CR2, NEF, DNG)
- Multi-threaded rendering with GPU acceleration
- Compatible with iOS 14.0+ and requires 2GB RAM

✅ Good Examples (User Benefits):

- Make any photo look professional in one tap
- Edit RAW files on your phone (not just JPGs)
- Preview edits in real-time without lag
- Works on any recent iPhone or iPad

Why it fails:

  • Technical language alienates casual users (your target)
  • Users can't visualize the benefit ("256-bit processing"-so what?)
  • Specs are checked *after* deciding to download, not before
  • Example: "GPU acceleration" matters; "makes editing instant" is what users want

The Translation Pattern:

Technical SpecUser Benefit
"EXIF data preservation""Keep photo location and date intact"
"32-bit color depth""Smooth gradients, no banding or color loss"
"Real-time collaborative editing""Edit with your team without emailing files back-and-forth"
"On-device processing (no cloud)""Your photos never leave your phone"

What to do instead:

  • Start with the job: What is the user trying to accomplish?
  • Translate feature → benefit: "Supports 50+ filters" → "Dozens of professional styles, instantly"
  • Use "so that" test: "Feature X, so that you can [benefit]" - if you can't complete it, it's not a benefit yet
  • Show before/after in copy if possible: "Turn blurry photos into magazine-quality shots"

5. Missing Localization Considerations (Cultural Tone Issues)

Problem: Copy written for US English doesn't translate culturally to other markets. Phrases that work in English sound off, awkward, or even tone-deaf in other languages and regions. Keyword searches also vary by locale.

❌ Bad Examples (US-Centric, Won't Translate Well):

- "The #1 photo app" (claims don't work globally; also unverifiable)
- "Crush your creative goals" (aggressive tone doesn't translate; weird in Japanese/German)
- "Slay your edits" (slang; meaningless in translation; age-specific)
- "Our app rocks" (informal; risky in formal markets like Germany/Japan)

✅ Good Examples (Culturally Neutral, Translates Well):

- "The most popular photo editor" (verifiable, neutral tone)
- "Achieve professional results in seconds" (universal benefit, formal enough)
- "Make every photo beautiful" (simple, universal, translates directly)
- "Trusted by millions worldwide" (global signal, works everywhere)

Common Localization Pitfalls:

MarketDon'tDo
GermanyAggressive slang ("crush," "slay")Professional, clear ("achieve," "optimize")
JapanBoastful claims ("best," "#1")Humble confidence ("trusted by millions," "preferred by")
BrazilFormal US EnglishWarm, conversational Portuguese (use native writer)
FranceEnglish marketing phrasesFrench alternatives (don't just translate)
China/AsiaWestern idioms (sports metaphors)Universal benefits without cultural references

Keyword Differences Across Regions:

  • US searches: "photo editor" (broad)
  • Germany searches: "Fotobearbeitung" (more specific; use region-native keyword research)
  • Japan searches: "写真編集" (completely different word choice needed)

❌ Bad Approach:

Write in US English → Translate to other languages → Done

(Loses cultural fit, tone, and keyword opportunity)

✅ Good Approach:

1. Write core value prop in neutral, translatable English
2. Have native speakers for each market adapt tone, keywords, and examples
3. Test keywords in each region's App Store search (not just Google)
4. Avoid slang, sports metaphors, US-specific references
5. Keep formal enough to work in risk-averse markets (Germany, Japan, Korea)

What to do instead:

  • Write neutral English first (works for the world)
  • Flag words/phrases that will need cultural adaptation ("#1," slang, US idioms)
  • For each locale: hire a native speaker to refine tone and keywords, not just translate
  • Keep tone at "professional confidence" level (works across cultures)
  • A/B test different tones in each market if feasible

Troubleshooting

Issue: Character Limit Errors After Generation

Symptoms: Copy looks great but exceeds App Store/Play Store field limits

Solution:

# Validate all fields at once
python scripts/check_app_store_limits.py --platform ios --input input.json

# Input format (input.json)
{
  "app_name": "YourApp",
  "subtitle": "Your subtitle text",
  "description": "Full description...",
  "keywords": "keyword,list,comma,separated"
}

# Or pipe from stdin
echo '{"app_name":"YourApp","subtitle":"Edit photos fast"}' | \
  python scripts/check_app_store_limits.py --platform ios --input -

# Google Play variant
python scripts/check_app_store_limits.py --platform google_play --input input.json

Quick fixes:

  • iOS subtitle (30 chars): Remove articles (a, the), use contractions
  • Google Play short desc (80 chars): Lead with strongest benefit
  • Keywords (100 chars iOS): Remove low-value keywords, use abbreviations

Issue: Generic/Bland Copy Despite Good Input

Symptoms: Generated copy sounds like every other app

Cause: Missing specific differentiators or proof points

Solution:

  1. Ask user: "What's one thing your app does that competitors don't?"
  2. Ask for numbers: "How many users? How much time saved?"
  3. Find the contrast: "What do users do today that sucks?"
  4. Example transform:

- Before: "Easy photo editing for everyone" - After: "Remove backgrounds in 2 taps—no expensive subscription"

Issue: Unclear Which Deliverables to Produce

Symptoms: User says "help with app marketing" without specifics

Solution: Present checklist and ask what they need:

  • iOS App Store listing
  • Google Play listing
  • Landing page hero copy
  • Screenshot captions
  • Social media ad hooks
  • Email campaign copy

Then produce only requested items.

Issue: Keyword Stuffing Creeping Back In

Symptoms: Copy passes limits but sounds unnatural

Cause: Trying to maximize keyword density

Solution:

  • Read copy aloud—if it sounds robotic, remove keywords
  • Each keyword should appear max 2× in subtitle+description combined
  • Use scripts/check_app_store_limits.py for length, but manually review readability
  • Ask: "Would a human actually say this?"

Issue: Missing References or Scripts

Symptoms: Skill mentions references/ or scripts/ files that don't exist

Solution:

  1. Check if files exist: ls skills/app-marketing-copy/references/
  2. If missing, proceed without them:

- Use inline limits instead of app-store-metadata.md - Manually validate character counts instead of running scripts

  1. Recommend to user: "For automated validation, create scripts/check_app_store_limits.py"

Included resources

  • references/app-store-metadata.md: field map + common limits + output skeletons.
  • references/screenshot-prompts.md: prompt templates for backgrounds and promo visuals.
  • scripts/check_app_store_limits.py: quick character-limit checker for iOS/Google Play fields (JSON in, table out).

适合场景

01

商品图处理

02

人像抠图

03

透明背景素材

04

营销设计资产

能力概览

能力 1

调用背景移除模型

能力 2

输出透明背景图片

能力 3

支持商品、人像和营销素材处理

能力 4

可接入图像编辑工作流

平台分布

Codex

34.59%
按下载量换算90

Claude

31.87%
按下载量换算83

Cursor

21.42%
按下载量换算55

Gemini CLI

9.44%
按下载量换算24

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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