ads-audit

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. Use when user says "audit", "full ad check", "analyze my ads", "account health check", or "PPC audit".

OpenClaw Conversion Notes

This skill was auto-converted from a Claude/BenAI-style skill into an OpenClaw-oriented skill file.

Use this skill with care:

• Treat Claude-specific command syntax (for example /skill ...) as intent hints, not literal required commands.
• Treat any allowed-tools, MCP, plugin, browser, .claude, or AskUserQuestion references as portability notes, not guaranteed runtime features.
• Before using referenced tools, verify they actually exist in the current OpenClaw session.
• Resolve any original .claude/... paths against the current OpenClaw workspace before use.
• If the skill references external APIs, credentials, connectors, or helper scripts, confirm local availability first.

Original Compatibility Warnings

• Original skill assumes external connectors, MCP servers, browser automation, or third-party integrations.

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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):
   • 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 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
5. Score — calculate per-platform and aggregate Ads Health Score (0-100)
6. 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