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ads-audit

ads-audit

github.com/hainrixzMarketing & growth10264 installsUpdated 3d ago
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About ads-audit

ads-audit is a multi-platform account audit skill for advertisers and marketing teams. It delegates checks across Google, Meta, and TikTok, then scores results and produces prioritized findings and quick wins.

Key features

  1. 01Collect exports, screenshots, or API data
  2. 02Delegate Google, Meta, and TikTok audits
  3. 03Validate and aggregate platform scores
  4. 04Generate reports and prioritized action plans
  5. 05Identify high-impact quick wins

Use cases

  1. 01Compare account health across ad platforms
  2. 02Find tracking, budget, or campaign-structure issues
  3. 03Prioritize urgent fixes and follow-up optimization

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/hainrixz/claude-ads --skill ads-audit

After installing, type/ads-auditin Claude Code to confirm it loaded.

Details

From the project README

Full Multi-Platform Ads Audit

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 (3 parallel deep specialists, one per platform):
    • audit-google: Conversion tracking, wasted spend, structure, keywords, ads, settings, PMax, AI Max, Demand Gen, CTV, YouTube video campaigns (G01-G74, G-PM*, G-AI*, G-DG*, G-CTV*)
    • audit-meta: Pixel/CAPI health, creative fatigue, structure, audience, Andromeda, Advantage+ (M01-M40, M-AN*, M-AT*, M-CR*, M-ST*, M-IA*, M-TH*) — MCP-wired
    • audit-tiktok: Pixel + Events API + ttclid, creative diversity, Smart+, GMV Max, Symphony, learning phase (T01-T25, T-SR*)
  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:

  • Meta Ads: Capa 1 (claude.ai Facebook MCP, free), Capa 2 (scripts/api/meta_fetch.py → meta-data.json), Capa 3 (Ads Manager export + Events Manager screenshot + EMQ)
  • Google Ads: Capa 1 (cohnen/mcp-google-ads, free), Capa 2 (scripts/api/google_fetch.py → google-data.json), Capa 3 (account export + Change History + Search Terms Report)
  • TikTok Ads: Capa 1 (AdsMCP/tiktok-ads-mcp, free), Capa 2 (scripts/api/tiktok_fetch.py → tiktok-data.json), Capa 3 (Ads Manager export + Pixel/Events API status)

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

Scoring

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

Per-Platform Weights
PlatformCategory Weights
GoogleConversion 25%, Waste 20%, Structure 15%, Keywords 15%, Ads 15%, Settings 10%
MetaPixel/CAPI 30%, Creative 30%, Structure 20%, Audience 20%
LinkedInTech 25%, Audience 25%, Creative 20%, Lead Gen 15%, Budget 15%
TikTokCreative 30%, Tech 25%, Bidding 20%, Structure 15%, Performance 10%
MicrosoftTech 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

Comments

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