ads-audit git:20260526.b91d55fA

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---
name: ads-audit
description: "Full multi-platform paid advertising audit with parallel subagent delegation. Analyzes Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads, and Apple Ads accounts via 7 parallel audit agents (incl. a regulatory-compliance agent for EU AI Act + US state privacy). Amazon Ads, cross-platform attribution, and server-side tracking are covered by their standalone sub-skills (ads-amazon, ads-attribution, ads-server-side-tracking) — Wave 3 will add their paired agents so they can dispatch in parallel here. Generates health score per platform and aggregate score (0-100). Use when user says audit, full ad check, analyze my ads, account health check, paid media audit, paid advertising audit, ad spend audit, advertising audit, or PPC audit."
user-invokable: false
tested_date: 2026-05-26
tested_with: claude-code v2.x
---

# Full Multi-Platform Ads Audit

This audit operates under the **10-Principle Thinking Framework** (see
`ads/references/thinking-framework.md`). OBSERVE (External + Internal)
dominates data collection, THINK + CONNECT (Lateral) dominate analysis,
CONNECT (System) + ACCEPT dominate synthesis and prioritization. If the
audit feels mechanical, you are skipping a principle.

## Process

1. **Collect account data**: request exports, screenshots, or API access
2. **Validate**: confirm at least one platform's data is available before proceeding
3. **Detect business type**: analyze account signals per ads orchestrator
4. **Identify active platforms**: determine which platforms are in use
5. **Delegate to subagents** (if available, otherwise run inline sequentially):
   - `audit-google`: Conversion tracking, wasted spend, structure, keywords, ads, settings (95 checks; G01-G95 incl. AI Max + GML 2026)
   - `audit-meta`: Pixel/CAPI health, creative fatigue, structure, audience (72 checks; M01-M72 incl. Andromeda + GEM + Lattice + ARM, MCP governance)
   - `audit-creative`: LinkedIn, TikTok, Microsoft creative checks + cross-platform synthesis
   - `audit-tracking`: LinkedIn, TikTok, Microsoft tracking + cross-platform tracking health
   - `audit-budget`: LinkedIn, TikTok, Microsoft budget/bidding + cross-platform allocation
   - `audit-policy-compliance`: Platform ad policies, Special Ad Categories, deprecated features, performance benchmarks
   - `audit-regulatory-compliance`: **New v1.8.0.** EU AI Act, 22-state US privacy, Privacy Sandbox shutdown, iOS 26, DSA, MCP write-action governance (C01-C29 + C-MCP-1..6)
6. **Validate**: verify each subagent returned valid scores with required fields before aggregating
7. **Score**: calculate per-platform and aggregate Ads Health Score (0-100)
8. **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
```