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Agent Skill

ads-google 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。

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

简介

ads-google 对 Google Ads 账户执行深度健康审计,覆盖 80 项关键指标评分。

  • 适用于需要全面诊断转化追踪、合规设置与广告表现的专业级广告账户分析。
  • 基于导出数据与基准值对比,输出 PASS/WARNING/FAIL 分类报告与行动建议。
  • 要求数据周期不少于 30 天且包含 Search Terms Report,否则无法启动分析。
  • 建议定期运行以监控账户健康度,结合 benchmarks.md 理解各项权重与行业基准。

SKILL.md

Google Ads Deep Analysis

Process

  1. Collect Google Ads account data (export, Change History, Search Terms Report)
  2. Validate: confirm data covers ≥30 days and includes Search Terms Report before proceeding
  3. Read ads/references/google-audit.md for full 80-check audit
  4. Read ads/references/benchmarks.md for Google-specific benchmarks
  5. Read ads/references/scoring-system.md for weighted scoring
  6. Evaluate all applicable checks as PASS, WARNING, or FAIL
  7. Validate: confirm all 80 checks evaluated before calculating score
  8. Calculate Google Ads Health Score (0-100)
  9. Generate findings report with action plan

What to Analyze

Conversion Tracking (25% weight)

  • Google tag (gtag.js) installed and firing on all pages
  • Enhanced Conversions active (hashed first-party data)
  • Consent Mode v2 implemented (required for EU/EEA)
  • Conversion actions mapped correctly (primary vs secondary)
  • Offline conversion import configured (for lead gen)
  • Server-side tagging via GTM (recommended for accuracy)
  • Attribution model: data-driven preferred (last-click as fallback only)
  • Conversion lag analysis (are conversions still trickling in?)

Wasted Spend (20% weight)

  • Search Terms Report reviewed (last 30 days minimum)
  • Negative keyword coverage adequate (shared lists + campaign-level)
  • Display placement audit (exclude low-quality sites)
  • Invalid click rate within norms (<10%)
  • Broad Match only used with Smart Bidding (NEVER without it)
  • Brand/non-brand campaigns separated
  • Geographic targeting precise (no wasted international spend)

Negative Keyword Rules (critical: bad negatives kill campaigns):

  • NEVER suggest Broad Match negatives unless explicitly justified; they block too broadly
  • Default to Exact Match [keyword] for specific irrelevant queries
  • Use Phrase Match "keyword" for irrelevant intent patterns
  • Source negatives from actual Search Terms Report irrelevant queries, NOT guesses
  • Group into themed lists: Informational (how-to, DIY, what is), Job-seeker (jobs, careers, salary), Competitor (only if intentionally excluded), Free-intent (free, crack, torrent)
  • Recommend Shared Negative Lists at the account level, not just campaign-level
  • Review existing negatives for over-blocking (are any negatives accidentally blocking converting queries?)

Account Structure (15% weight)

  • Campaign-level organization follows business logic
  • Ad groups themed tightly (15-20 keywords max per group)
  • RSA ad groups have ≥3 active ads
  • PMax campaigns structured correctly (asset groups, signals)
  • SKAGs evaluated (migrate to themed groups if present)
  • Campaign labels/naming conventions consistent

Keywords (15% weight)

  • Match type strategy appropriate (Exact → Phrase → Broad progression)
  • Quality Score distribution (aim ≥7 average)
  • Low QS keywords flagged (<5 = FAIL, 5-6 = WARNING)
  • Keyword cannibalization check (same keywords in multiple campaigns)
  • Impression share tracked for top keywords
  • Keyword bid adjustments set for devices/locations/audiences

Ads (15% weight)

  • RSA: ≥8 unique headlines, ≥3 descriptions per ad group
  • RSA: ad strength "Good" or "Excellent" (not "Poor" or "Average")
  • Pin usage minimal and strategic (over-pinning reduces RSA flexibility)
  • Ad extensions: sitelinks (≥4), callouts (≥4), structured snippets, image
  • Dynamic keyword insertion used appropriately
  • Ad copy includes CTA, value proposition, differentiators

Settings (10% weight)

  • ECPC (Enhanced CPC) flagged as deprecated. Migrate to full Smart Bidding (tCPA/tROAS/Maximize)
  • Bid strategy appropriate for campaign maturity and goals
  • Budget pacing: no campaigns limited by budget (unless intentional)
  • Ad schedule aligned with business hours/conversion patterns
  • Device bid adjustments set based on performance data
  • Location targeting: "Presence" not "Presence or Interest"
  • Network settings: Search Partners reviewed, Display opt-out for Search

GAQL & Data Accuracy

Before analyzing data, read ads/references/gaql-notes.md for known GAQL field incompatibilities, deduplication patterns, and filter scope best practices. Key rules:

  • Deduplicate keywords by (ad_group_id + keyword_text + match_type) before any analysis
  • Only analyze ENABLED campaigns and ad groups (exclude paused/removed)
  • Filter to keywords with impressions > 0 for theme coherence checks (G03)
  • Apply legacy BMM heuristic: BROAD + Manual CPC = legacy BMM, not intentional broad (G17)
  • Only flag wasted spend on terms with >$10 spend AND 0 conversions (G16)
  • Count shared negative keyword lists alongside campaign-level negatives (G14/G15)

Google Ads MCP Integration (Optional)

For automated data collection, connect the Google Ads MCP server:

  • Tools available: search (GAQL queries), list_accessible_customers
  • Setup: Configure in .mcp.json or Claude Code MCP settings
  • Customer ID: Extract from CLAUDE.md under Accounts > Google Ads, or ask the user
  • Fallback: If MCP is not configured, fall back to manual data export (the default workflow)

When MCP is available, use it to pull Search Terms Reports, keyword data, conversion actions, and campaign structure automatically instead of requiring manual exports.

PMax Deep Dive

If Performance Max campaigns exist, additionally evaluate:

  • Asset group diversity (text, images, video, feeds)
  • Audience signals configured (custom segments, lists, demographics)
  • URL expansion settings reviewed (opt-out of irrelevant pages)
  • Brand exclusions applied (prevent cannibalizing brand search), available for all advertisers
  • Campaign-level negative keywords now available for ALL advertisers
  • Search themes utilized (2024 feature)
  • Final URL expansion: enabled or disabled with justification
  • Insights tab reviewed (search categories, audience segments)

AI Max for Search (2026)

AI Max layers broad match + keywordless targeting on existing Search campaigns. 14% avg conversion lift. DSA likely consolidated into AI Max Q2 2026. Requires strong negative keyword lists.

If AI Max for Search is available/active:

  • Broad Match + AI Max integration evaluated
  • Auto-generated headline performance monitored
  • Search term categories reviewed for relevance
  • Budget impact assessed (AI Max can shift spend)
  • Negative keyword lists reviewed for completeness (AI Max broadens reach significantly)
  • DSA migration path assessed (consolidation expected Q2 2026)

Demand Gen Campaigns

Replaced Video Action Campaigns (April 2026). Video + image = 20% more conversions. Frequency capping NOT supported.

If Demand Gen campaigns exist, evaluate:

  • Video + image asset mix present (combined format drives 20% more conversions)
  • Audience signals configured (custom segments, lookalikes)
  • Conversion tracking aligned with upper/mid-funnel goals
  • Note: frequency capping is not available. Monitor reach vs frequency manually

Key Thresholds

MetricPassWarningFail
Quality Score (avg)≥75-6<5
CTR (Search)≥6.66%3-6.66%<3%
CVR (Search)≥7.52%3-7.52%<3%
CPC (Search)≤$5.26$5.26-8.00>$8.00
Wasted Spend<10%10-20%>20%
Ad StrengthGood+AveragePoor
Invalid Clicks<5%5-10%>10%

Output

Google Ads Health Score

Google Ads Health Score: XX/100 (Grade: X)

Conversion Tracking: XX/100  ████████░░  (25%)
Wasted Spend:        XX/100  ██████████  (20%)
Account Structure:   XX/100  ███████░░░  (15%)
Keywords:            XX/100  █████░░░░░  (15%)
Ads:                 XX/100  ████████░░  (15%)
Settings:            XX/100  ██████████  (10%)

Deliverables

  • GOOGLE-ADS-REPORT.md: Full 80-check findings with pass/warning/fail
  • Wasted spend estimate (monthly $ value)
  • Quick Wins sorted by impact
  • PMax-specific recommendations (if applicable)
  • Keyword health matrix with QS, CTR, CVR per keyword group

适合场景

01

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

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

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

34.36%
按下载量换算1,284

Claude

32.54%
按下载量换算1,216

Cursor

19.41%
按下载量换算725

Gemini CLI

8.39%
按下载量换算313

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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