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ads-audit

@naveedharri · 收录于 1 周前

Full multi-platform paid advertising audit with parallel subagent delegation. Analyzes Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, and Microsoft Ads accounts. Generates health score per platform and aggregate score. Use when user says "audit", "full ad check", "analyze my ads", "account health check", or "PPC audit".

适合你,如果管理多个广告平台并需要定期审计账户表现。

/ 下载安装
ads-audit.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add naveedharri/benai-skills/ads-audit
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- naveedharri/benai-skills/ads-audit
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify naveedharri/benai-skills/ads-audit
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
37GitHub stars
~837上下文体积 · 单文件
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怎么用

技能原文 SKILL.md作者撰写 · MIT · 946a3d7

Full Multi-Platform Ads Audit

Process
  1. Collect account data — request exports, screenshots, or API access
  2. Detect business type — analyze account signals per ads orchestrator
  3. Identify active platforms — determine which platforms are in use
  4. Delegate to subagents (if available, otherwise run inline sequentially):
  5. audit-google — Conversion tracking, wasted spend, structure, keywords, ads, settings (G01-G74)
  6. audit-meta — Pixel/CAPI health, creative fatigue, structure, audience (M01-M46)
  7. audit-creative — LinkedIn, TikTok, Microsoft creative checks + cross-platform synthesis
  8. audit-tracking — LinkedIn, TikTok, Microsoft tracking + cross-platform tracking health
  9. audit-budget — LinkedIn, TikTok, Microsoft budget/bidding + cross-platform allocation
  10. audit-compliance — All-platform compliance, settings, performance benchmarks
  11. Score — calculate per-platform and aggregate Ads Health Score (0-100)
  12. Report — generate prioritized action plan with Quick Wins
Data Collection

Ask the user for available data. Accept any combination:

  • Google Ads: account export, Change History, Search Terms Report
  • Meta Ads: Ads Manager export, Events Manager screenshot, EMQ scores
  • LinkedIn Ads: Campaign Manager export, Insight Tag status
  • TikTok Ads: Ads Manager export, Pixel/Events API status
  • Microsoft Ads: account export, UET tag status, import validation results

If no exports available, audit from screenshots or manual data entry.

Scoring

Read ads/references/scoring-system.md for full algorithm.

Per-Platform Weights

| Platform | Category Weights | |----------|-----------------| | Google | Conversion 25%, Waste 20%, Structure 15%, Keywords 15%, Ads 15%, Settings 10% | | Meta | Pixel/CAPI 30%, Creative 30%, Structure 20%, Audience 20% | | LinkedIn | Tech 25%, Audience 25%, Creative 20%, Lead Gen 15%, Budget 15% | | TikTok | Creative 30%, Tech 25%, Bidding 20%, Structure 15%, Performance 10% | | Microsoft | Tech 25%, Syndication 20%, Structure 20%, Creative 20%, Settings 15% |

Aggregate Score
Aggregate = Sum(Platform_Score x Platform_Budget_Share)
Grade: A (90-100), B (75-89), C (60-74), D (40-59), F (<40)
Output Files
  • ADS-AUDIT-REPORT.md — Comprehensive multi-platform findings
  • ADS-ACTION-PLAN.md — Prioritized recommendations (Critical > High > Medium > Low)
  • ADS-QUICK-WINS.md — Items fixable in <15 minutes with high impact
Report Structure
Executive Summary
  • Aggregate Ads Health Score (0-100) with grade
  • Per-platform scores
  • Business type detected
  • Active platforms identified
  • Top 5 critical issues across all platforms
  • Top 5 quick wins across all platforms
Per-Platform Sections

Each platform section includes:

  • Platform Health Score with grade
  • Category breakdown with pass/warning/fail per check
  • Platform-specific Quick Wins
  • Detailed findings with remediation steps
Cross-Platform Analysis
  • Budget allocation assessment (actual vs recommended)
  • Tracking consistency (are all platforms tracking the same events?)
  • Creative consistency (is messaging aligned across platforms?)
  • Attribution overlap (are platforms double-counting conversions?)
Strategic Recommendations
  • Platform prioritization based on business type
  • Budget reallocation recommendations
  • Scaling opportunities (platforms/campaigns ready to scale)
  • Kill list (campaigns/ad groups to pause immediately)
Priority Definitions
  • Critical: Revenue/data loss risk (fix immediately)
  • High: Significant performance drag (fix within 7 days)
  • Medium: Optimization opportunity (fix within 30 days)
  • Low: Best practice, minor impact (backlog)
Quick Wins Criteria
IF severity == "Critical" OR severity == "High"
AND estimated_fix_time < 15 minutes
THEN flag as Quick Win
SORT BY (severity_multiplier x estimated_impact) DESC
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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