ads-audit

Full multi-platform paid advertising audit with parallel subagent delegation. Analyzes Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads, and Apple…

INSTALLATION
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-audit
Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

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

  • Collect account data: request exports, screenshots, or API access
  • Validate: confirm at least one platform's data is available before proceeding
  • Detect business type: analyze account signals per ads orchestrator
  • 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 (80 checks; G01-G61 + 19 hyphenated v1.5+ IDs incl. AI Max)
  • audit-meta: Pixel/CAPI health, creative fatigue, structure, audience (50 checks; M01-M40 + 10 hyphenated v1.5+ IDs incl. Andromeda)
  • 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-compliance: All-platform compliance, settings, performance benchmarks
  • Validate: verify each subagent returned valid scores with required fields before aggregating
  • 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

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
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