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app-store-optimizer应用商店优化器

Agent Skill

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。

总安装

8,837

周安装

361

GitHub Stars

公开资料未说明

下载量

2,830
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

70.57%
按下载量换算1,997

安全审计

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通过

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通过

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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

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