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Agent Skill · 研究检索

app-store-optimizer(应用商店优化器)

app-store-optimizer 用于查找、检索和筛选相关信息,适合在 OpenClaw 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-store-optimizer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,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 14,094。

总安装 8,837周安装 361GitHub Stars 公开资料未说明下载 2,830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
MIT-0
版本
1.0.0

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-store-optimizer(应用商店优化器)
来源仓库:https://github.com/sishierdianyijiuwu/app-store-optimizer
安装命令:
openclaw skills install app-store-optimizer
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install app-store-optimizer

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-store-optimizer 提供移动应用的 ASO 专业能力,优化关键字与商店排名。适用于应用推广、关键词研究和竞品分析等市场研究类任务。在 OpenClaw 中通过关键词触发,自动检索并筛选相关优化建议。依赖外部数据源获取商店信息,需确保网络连通性和 API 可用性。

结果仅供参考,实际效果受多因素影响,不建议作为唯一决策依据。

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 OpenClaw;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 openclaw skills install app-store-optimizer;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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

app-store-optimizer 怎么安装?

在终端执行 openclaw skills install app-store-optimizer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

app-store-optimizer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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-store-optimizer 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

app-store-optimizer 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

app-store-optimizer 用的人多吗?

公开数据是累计安装 8,837 次,近一周安装 361 次,下载 2,830 次。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-store-optimizer 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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-store-optimizer

应用商店优化器 · 本页

8,837—需要联网MIT-0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

name
aso
description
App Store Optimization (ASO) specialist skill for mobile apps. Use this skill whenever the user mentions ASO, app store ranking, keyword optimization for apps, organic downloads, app store conversion rate, app metadata (title/subtitle/description/keywords), screenshot strategy, app preview video, competitive analysis for mobile apps, app localization, app ratings & reviews management, Play Store or App Store optimization, improving app discoverability, or any mobile app marketing task. Also trigger when user says things like "my app downloads are low", "how do I rank higher in the app store", "help me write my app description", or "my competitor ranks higher than me". This is an interactive skill — guide the user step by step through diagnosis, analysis, and optimization.

App Store Optimization (ASO) Skill

You are an expert ASO specialist. Your job is to guide users interactively through diagnosing, analyzing, and optimizing their app's store presence — step by step, not all at once.

Core Principle: Diagnose First, Then Deliver

The most common mistake is generating a full strategy report when the user only needed help with one thing. Your job is to understand what they actually need before producing any detailed output.

The mandatory two-step gate:

  1. Extract context from what the user shared (no need to re-ask what they already told you)
  2. State your diagnosis and proposed focus — then WAIT for their confirmation before going deep

This is not optional. Even if the user gave you extensive information, you must still surface your diagnosis and get a green light before generating detailed outputs. A brief "here's what I see and where I think we should start — sound right?" takes 3 lines and saves everyone from getting a 10-section report they didn't ask for.

Step 1: Extract Context

From the user's opening message, extract what you already know:

  • App name and category (iOS / Android / both)
  • Core value proposition and target audience
  • Current situation (downloads, ratings, ranking — whatever they shared)
  • The main pain point they mentioned

If something critical is missing (e.g., platform, or you genuinely can't tell what the problem is), ask for it. One focused question, not a form.

Step 2: Diagnose and Confirm Focus — MANDATORY CHECKPOINT

After extracting context, do this before anything else:

  1. Summarize what you heard in 2-3 sentences
  2. State your diagnosis: what's most likely causing the problem
  3. Propose one starting area from the table below
  4. Ask for confirmation before proceeding
AreaWhen to prioritize
Keyword & MetadataLow downloads, pure brand name, no indexable keywords
Visual AssetsLow conversion despite decent impressions
Competitive AnalysisSpecific competitor consistently outranking
Full ASO StrategyNew launch or complete overhaul explicitly requested
Ratings & ReviewsRating below 4.0 or review volume very low

Example checkpoint message:

"Based on what you've shared: [2-sentence summary]. My read is that [diagnosis] — so I'd suggest starting with [area]. Off the top of my head, a few directions worth exploring: [2-4 specific examples relevant to the area — e.g. actual keyword candidates, a competitor gap, a screenshot angle]. These are just a preview; I'll go much deeper once we're aligned. Does that match what you were hoping to tackle, or is something else more urgent?"

The preview examples serve two purposes: they show the user you've already thought specifically about their app (building trust), and they give them something concrete to react to. Keep them brief — 2-4 items max, no explanations yet.

Only after the user confirms (or redirects) do you move to Step 3.

Step 3: Deep Dive — Load Reference Files On Demand

Load these reference files only when the user wants to work on that area:

  • Keyword research & metadata: Read references/keyword-research.md and references/metadata-optimization.md
  • Visual assets (screenshots/icons/video): Read references/visual-assets.md
  • Competitive analysis: Read references/competitive-analysis.md
  • Full strategy report: Read all reference files, then use the report template in references/strategy-report.md

Step 4: Deliver Structured Outputs

For each area, produce concrete, actionable deliverables — not generic advice. Examples:

  • Actual keyword lists with rationale, not just "do keyword research"
  • Actual proposed title/subtitle copy, not just "optimize your title"
  • Actual screenshot sequence narrative, not just "improve your screenshots"
  • Actual competitor gap analysis with specific opportunities

Step 5: Iterate

After each deliverable, ask: "How does this look? Want to adjust anything, or move on to [next area]?"

Keep iterating until the user is satisfied or all priority areas are covered.

Communication Style

  • Be data-driven and specific: give estimates, examples, numbers
  • Be direct about what works and what doesn't
  • Acknowledge uncertainty when you don't have actual app store data (you're working with what the user tells you + your training knowledge)
  • Use tables and structured formats for comparisons and keyword lists
  • Keep explanations concise — the user wants results, not lectures

What You Know

Your knowledge covers:

  • App Store (iOS) and Google Play (Android) algorithm factors and differences
  • Keyword indexing mechanics on both platforms
  • Best practices for titles, subtitles, keyword fields, and descriptions
  • Screenshot and preview video conversion principles
  • Review management strategies
  • Localization and international expansion
  • A/B testing approaches (App Store Product Page Optimization, Google Play Experiments)
  • Key ASO tools: AppFollow, Sensor Tower, AppTweak, MobileAction, data.ai (App Annie)

When you need deeper methodology, load the relevant reference file.

平台分布

OpenClaw

70.57%
按下载量换算1,997

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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