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ads-audit

Name: Ads Audit
Author: AgriciDaniel

// 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 6 parallel audit agents. 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.

Manus에서 실행

$ git log --oneline --stat

stars:5,162

forks:788

updated:2026년 5월 18일 09:29

SKILL.md

readonly

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 6 parallel audit agents. 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	"2026-05-17T00:00:00.000Z"
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

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

related-skills.json

같은 저장소

ads.md

from "AgriciDaniel/claude-ads"

Multi-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, and Amazon Ads. 250+ checks with scoring, parallel agents, industry templates, AI creative generation, attribution and server-side tracking deep dives.

2026-05-185.2k

ads-create.md

from "AgriciDaniel/claude-ads"

Campaign concept and copy brief generator for paid advertising. Reads brand-profile.json and optional audit results to produce structured campaign concepts, messaging pillars, and copy briefs. Outputs campaign-brief.md to the current directory. Run after /ads dna and before /ads generate. Triggers on: create campaign, campaign brief, ad concepts, write ad copy, campaign strategy, ad messaging, creative brief, generate concepts.

2026-05-185.2k

ads-dna.md

from "AgriciDaniel/claude-ads"

Brand DNA extractor for paid advertising. Scans a website URL to extract visual identity, tone of voice, color palette, typography, and imagery style. Outputs brand-profile.json to the current directory. Run before /ads create or /ads generate for brand-consistent creative. Triggers on: brand DNA, brand profile, extract brand, brand identity, brand colors, what is the brand voice, analyze brand, brand style guide.

2026-05-185.2k

ads-plan.md

from "AgriciDaniel/claude-ads"

Strategic paid advertising planning with industry-specific templates. Covers platform selection, campaign architecture, budget planning, creative strategy, and phased implementation roadmap. Use when user says ad plan, ad strategy, campaign planning, media plan, PPC strategy, or advertising plan.

2026-05-185.2k

ads-apple.md

from "AgriciDaniel/claude-ads"

Apple Ads (formerly Apple Search Ads) deep analysis for mobile app advertisers. Evaluates campaign structure, bid health, Custom Product Pages (CPPs), AdAttributionKit (view-through attribution 24h post-impression), MMP attribution, budget pacing, TAP coverage (Today/Search/Product Pages), Maximize Conversions bidding, and goal CPA benchmarks by country. Use when user says Apple Ads, Apple Search Ads, ASA, App Store ads, Apple ads, Search Ads, AdAttributionKit, view-through attribution, or is advertising a mobile app on iOS.

2026-05-185.2k

ads-budget.md

from "AgriciDaniel/claude-ads"

Budget allocation and bidding strategy review across all ad platforms. Evaluates spend distribution, bidding strategy appropriateness, scaling readiness, and identifies campaigns to kill or scale. Uses 70/20/10 rule, 3x Kill Rule, and 20% scaling rule. Use when user says budget allocation, bidding strategy, ad spend, ROAS target, media budget, or scaling.

2026-05-185.2k

package.json

"author": "AgriciDaniel"

"repository": "AgriciDaniel/claude-ads"

GitHub 저장소 열기 Creator 저장소 보기

$ install --global

$ download --local

Manus에서 실행

$ useful --forSOC

시장조사 분석가·마케팅 전문가비즈니스 및 금융 운영직13-1161L4

ads-audit

Full Multi-Platform Ads Audit

Process

Data Collection

Scoring

Per-Platform Weights

Aggregate Score

Output Files

Report Structure

Executive Summary

Per-Platform Sections

Cross-Platform Analysis

Strategic Recommendations

Priority Definitions

Quick Wins Criteria

이 저장소의 다른 Skills

이 저장소의 다른 Skills

Full Multi-Platform Ads Audit

Process

Data Collection

Scoring

Per-Platform Weights

Aggregate Score

Output Files

Report Structure

Executive Summary

Per-Platform Sections

Cross-Platform Analysis

Strategic Recommendations

Priority Definitions

Quick Wins Criteria