| name | ads audit |
| description | 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. Triggers on: "audit", "full ad check", "analyze my ads", "account health check", "PPC audit", "ad account audit"
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/ads audit — Full Multi-Platform Ads Audit
Comprehensive paid media audit across all active advertising platforms.
Usage
/ads audit
/ads audit --platforms google meta
Process
- Collect account data — request exports, screenshots, or API access
- Detect business type — analyze account signals
- Identify active platforms — determine which platforms are in use
- Delegate to subagents (if available, otherwise run inline sequentially):
audit-google — Conversion tracking, wasted spend, structure, keywords, ads, settings (G01-G74)audit-meta — Pixel/CAPI health, creative fatigue, structure, audience (M01-M46)audit-creative — LinkedIn, TikTok, Microsoft creative checks + cross-platform synthesisaudit-tracking — LinkedIn, TikTok, Microsoft tracking + cross-platform tracking healthaudit-budget — LinkedIn, TikTok, Microsoft budget/bidding + cross-platform allocationaudit-compliance — All-platform compliance, settings, performance benchmarks
- Score — calculate per-platform and aggregate Ads Health Score (0-100)
- 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
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 findingsADS-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
