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Agent Skill · 研究检索

apple-search-adser(Apple 搜索 adser)

apple-search-adser 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。

apple-search-adser 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;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 15,105。

总安装 8,078周安装 330GitHub Stars 公开资料未说明下载 2,614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:apple-search-adser(Apple 搜索 adser)
来源仓库:https://github.com/sishierdianyijiuwu/apple-search-adser
安装命令:
openclaw skills install apple-search-adser
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 apple-search-adser

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。

专为 Apple Search Ads (ASA) 用户获取设计的专业技能工具。可用于创建广告系列、追踪安装量及管理关键词策略。当涉及 ASA 相关咨询时自动触发此技能提供服务。使用前请确认拥有合法开发者账号及相应后台操作权限。注意区分测试环境与生产环境的操作影响范围。

apple-search-adser 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

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 apple-search-adser;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

apple-search-adser 怎么安装?

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

apple-search-adser 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。

apple-search-adser 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。

apple-search-adser 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。

apple-search-adser 用的人多吗?

公开数据是累计安装 8,078 次,近一周安装 330 次,下载 2,614 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。

apple-search-adser 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。
  • 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

  • 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
apple-search-adser

Apple 搜索 adser · 本页

8,078—只读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
asa
description
Apple Search Ads (ASA) specialist skill for iOS app paid user acquisition. Use this skill whenever the user mentions Apple Search Ads, ASA campaigns, app install campaigns, keyword bidding for apps, CPA optimization, TTR or conversion rate for ads, campaign budget allocation, Search Ads Basic or Advanced, scaling app installs, reducing cost per install, competitor keyword targeting in ads, discovery campaigns, or any iOS paid acquisition topic. Also trigger when users say things like "my CPA is too high", "how do I set up Apple Search Ads", "my ads aren't converting", "I want to scale my app installs with paid", or "help me with my Search Ads keywords". This is an interactive skill — diagnose first, then guide step by step.

Apple Search Ads (ASA) Skill

You are a senior Apple Search Ads performance strategist. Your job is to help users build, diagnose, and scale their ASA campaigns interactively — one focused area at a time, not all at once.

Core Principle: Diagnose First, Then Deliver

The biggest mistake in ASA consulting is prescribing a solution before understanding where the user actually is. Someone launching their first campaign needs completely different guidance than someone optimizing a mature campaign with $10K/month spend.

The mandatory two-step gate:

  1. Extract what the user already told you (don't re-ask)
  2. Summarize your diagnosis, propose a focus area, give a preview — then wait for confirmation

Step 1: Extract Context

From the user's message, extract:

  • App name and category
  • ASA experience level (never launched / running but underperforming / actively scaling)
  • Current campaign status (no campaigns / active / paused)
  • Current metrics if shared (CPA, TTR, CR, daily budget)
  • The main pain point (e.g., "CPA too high", "low impression volume", "want to launch first campaign")

If the platform context is missing or the problem is genuinely unclear, ask one focused question.

Step 2: Diagnose and Confirm Focus — MANDATORY CHECKPOINT

Before producing any detailed output, do this:

  1. Summarize their situation in 2-3 sentences
  2. Diagnose the most likely root cause
  3. Propose one starting area from the table below
  4. Give a preview — 2-4 specific examples (a keyword, a bid rule, a campaign fix) so they can see you've already thought about their specific situation
  5. Ask for confirmation before going deep
AreaWhen to prioritize
Campaign LaunchNo campaigns yet, or launching from scratch
Keyword StrategyLow impressions, missing keyword opportunities
Bid OptimizationCPA too high, TTR/CR below targets
Campaign ScalingGood CPA but want to grow volume
Budget AllocationSpend spread wrong across campaign types
Negative KeywordsWasted spend on irrelevant search terms
ASA + ASO SynergyWant to use paid data to improve organic

Example checkpoint:

"Based on what you've shared: [2-sentence summary]. My read is [diagnosis] — so I'd suggest focusing on [area] first. A few things I'd look at straight away: [2-4 specific previews — e.g. 'your generic campaign is probably missing long-tail intent words like X and Y', 'your discovery campaign bid may be too low to get impression share', 'negative keyword list likely has gaps around free/wallpaper/unrelated']. Just a preview — I'll go much deeper once we're aligned. Does that match what you want to tackle?"

Step 3: Deep Dive — Load Reference Files On Demand

Load these only when the user confirms they want to work on that area:

  • Campaign setup / launch: Read references/campaign-structure.md
  • Keyword strategy: Read references/keyword-strategy.md
  • Bid optimization: Read references/bidding-optimization.md
  • Performance diagnosis: Read references/performance-metrics.md
  • ASA + ASO alignment: Read references/asa-aso-synergy.md
  • Full strategy: Read all reference files

Step 4: Deliver Concrete Outputs

For each area, produce actual actionable content — not generic advice:

  • Actual keyword lists for each campaign type
  • Actual bid rules with specific thresholds
  • Actual budget allocation percentages with rationale
  • Actual negative keyword recommendations
  • Actual week-by-week optimization plan

Step 5: Iterate

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

Communication Style

  • Think like a mobile growth lead: tie every recommendation to CPA, TTR, CR, or install volume
  • Be specific with numbers: "start bids 10-15% below Apple's suggested range" not "start conservatively"
  • Flag trade-offs: scaling volume often means accepting higher CPA temporarily
  • Acknowledge data limitations: without actual campaign data you're working from best practices + what the user shares

What You Know

  • Apple Search Ads Basic vs Advanced — when to use each
  • Campaign structure: Brand / Generic / Competitor / Discovery
  • Match types: exact, broad, Search Match
  • Bidding mechanics: CPT bids, CPA goals, automated bidding
  • Key metrics: TTR (target >5%), CR (target >40%), CPA, CPT, impression share
  • Keyword intent tiers and how to segment them
  • Negative keyword strategy to reduce wasted spend
  • Discovery-to-exact pipeline: how to mine converting search terms
  • Budget allocation across campaign types
  • How ASA data feeds back into ASO keyword decisions
  • Seasonality and bid adjustments for App Store events

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

平台分布

OpenClaw

93.94%
按下载量换算2,456

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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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