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google-adsGoogle Ads 搜索

Agent Skill

google-ads 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。

总安装

17,582

周安装

740

GitHub Stars

409

下载量

6,157
CodexClaudeCursorGemini CLI

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

unknown

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:google-ads(Google Ads 搜索)
来源仓库:https://github.com/kostja94/marketing-skills
仓库路径:skills/google-ads
安装命令:
npx skills add https://github.com/kostja94/marketing-skills --skill google-ads
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/kostja94/marketing-skills --skill google-ads

简介

google-ads 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。

  • 适用于 Google Ads 策略、广告文案优化和投放效果分析等营销研究场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需确认权限范围和维护状态。
  • 使用前建议核对是否会触发联网、命令执行或文件读写操作。
  • google-ads 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Paid Ads: Google Ads

Guides Google Ads setup, campaign structure, keyword targeting, and optimization. Google Ads excels at high-intent search traffic; use when people actively search for your solution.

When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.

Two Modes: PMF Testing vs Conversion-Driven

ModeWhenBudgetLanding pageMetrics
PMF testingPre-PMF; validate idea before building$47–500; start smallSimple LP: headline, benefits, problem solved, CTA ("Join Waitlist," "Get Early Access")CTR, sign-up rate, bounce rate; low CTR/high bounce = messaging/positioning issue
Conversion-drivenPMF validated; commercializationScale; ROAS targetFull funnel; ad-to-page alignmentROAS, CAC, conversion rate

PMF testing: No full product needed. Build landing page with Unbounce, Carrd, or Webflow. Run ads to relevant search terms; measure clicks, engagement, signups. Test messaging (e.g., "Fastest App for Freelancers" vs "Simplest Time Tracker for Teams"), pricing (different price points in ads/LP), and audiences (keyword targeting, in-market). Allow 4–6 weeks for PMax learning phase. Use as learning tool, not just marketing channel.

Reference: Marketing Cactus – Using Google Ads to Test Product-Market Fit

Campaign Structure

Account
├── Campaign: Brand (Search)
├── Campaign: Non-Brand (Search)
├── Campaign: Competitor (Search) — optional; bid on competitor brand + "alternative"/"vs"
├── Campaign: Retargeting (Display)
└── Campaign: Performance Max

Competitor Brand Keywords

When: Bid on "[Competitor] alternative," "[Competitor] vs [You]" to intercept high-intent traffic. Google allows competitor terms as keywords; you cannot use competitor names in ad copy without permission.

Landing page: Use a dedicated landing page (comparison/alternatives page), not a blog article. Users searching competitor brands expect direct alternatives—a blog increases bounce; a comparison page matches intent and converts better. See alternatives-page-generator for structure.

Best practices:

  • Separate campaign; exact/phrase match; add your brand as negative
  • H1 mirrors search intent (e.g., "[Competitor] vs [You]")
  • Feature comparison table; one-line differentiator; strong CTA
  • Expect lower Quality Score, higher CPC than non-brand; optimize LP relevance

Naming: GOOG_[Objective]_[Audience]_[Offer]_[Date] (e.g., GOOG_Search_Brand_Demo_Ongoing)

Campaign Types

TypeBest for
SearchHigh-intent queries; keyword-targeted; landing page critical
DisplayAwareness; retargeting; broader reach
YouTubeVideo; awareness; consideration
Performance MaxAutomated; cross-channel; feed + search + display

Performance Max (PMax) Optimization

Learning period: Run at least 6 weeks for algorithm ramp-up. Works best as complement to Search, not replacement.

Asset groups: Organize by *audience intent* (e.g., high-intent searchers, cart abandoners, category researchers), not product category alone. Audience signals improve CPA and ROAS vs. no signals.

Asset requirements (per asset group):

  • ≥5 images (include 1200×1200)
  • ≥5 text assets (4 headlines, 5 descriptions)
  • Video when possible
  • Refresh creative regularly to maintain performance

Signals: Add remarketing lists and Customer Match to accelerate learning.

Weekly health check: Flag if brand terms >30% of conversions; unexpected geo conversions; any placement >15% of total spend; asset group performance below "Good."

Keyword Strategy

  • Brand: Protect brand terms; exclude from non-brand campaigns
  • Negative keywords: Build weekly; avoid irrelevant queries. Add support terms (login, forum, pricing, help) from keyword-research—these are existing customers, not prospects.
  • Match types: Broad (discovery) → Phrase → Exact (control)

Keyword sources: Use keyword-research for keyword list, clusters, and intent. Map each cluster to a dedicated landing page; relevance improves Quality Score and lowers CPC.

Quality Score Levers

FactorAction
Expected CTRImprove ad relevance; test headlines
Ad relevanceAlign ad copy to keyword intent
Landing pageAd-to-page alignment; fast load; mobile-friendly

Target: Quality Score ≥6; higher = lower CPC, better ad rank. Benchmark: Improving Quality Score from 5 to 7 can reduce CPC by 30–50%.

Bidding Strategy

Conversions/monthStrategy
<30Manual CPC (smart bidding needs volume to optimize)
30–50Target CPA; minimum for effective smart bidding
50–100Target CPA
100+Target ROAS

Smart bidding: AI-powered bidding (Target CPA, Target ROAS) typically delivers better ROI than manual when conversion volume is sufficient; requires ≥30 conversions in 30 days to work effectively.

Tracking

  • Enhanced Conversions: Server-side signals for better attribution
  • Offline conversion imports: B2B; CRM → Google Ads
  • UTM: Consistent parameters for GA4 cross-check

Paid–Organic Cannibalization

When you rank organically (position 4+) for a keyword and also run PPC, paid ads can absorb clicks that would go to organic. Audit: Cross-reference GSC organic rankings with Search Terms report. If organic ranks well, test pausing PPC on those terms to free budget for higher-impact keywords.

Reference: Backlinko – SEO and PPC: 8 Smart Ways to Align

Pre-Launch Checklist

  • Conversion tracking tested with real conversion
  • Landing page loads <3s; mobile-friendly
  • UTM parameters working
  • Negative keyword list built (include support terms from keyword-research)
  • Budget set; targeting matches audience

Related Skills

  • pmf-strategy: PMF validation framework; when to use PMF testing vs conversion-driven
  • paid-ads-strategy: Channel selection; budget allocation; ad-to-page alignment; competitor brand bidding
  • alternatives-page-generator: Competitor brand keyword ads → dedicated LP (not blog); comparison page structure
  • keyword-research: Keyword list, clusters, intent; support terms for negative keywords; PPC data feeds back SEO priority
  • traffic-analysis: UTM for attribution; paid–organic cannibalization audit
  • landing-page-generator: LP structure for paid traffic; PAA → FAQ
  • analytics-tracking: Conversion tracking; ROAS measurement

适合场景

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用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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能力概览

能力 1

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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

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

Codex

32.4%
按下载量换算1,995

Claude

31.05%
按下载量换算1,912

Cursor

18.86%
按下载量换算1,161

Gemini CLI

9.41%
按下载量换算579

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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