Install
$ agentstack add skill-maxymize-maxym-ai-ads-ads-audit ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Full Multi-Platform Ads Audit
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 (G01-G74)audit-meta: Pixel/CAPI health, creative fatigue, structure, audience (M01-M46)audit-creative: LinkedIn, TikTok, Microsoft creative checks + cross-platform synthesisaudit-tracking: LinkedIn, TikTok, Microsoft tracking + cross-platform tracking healthaudit-budget: LinkedIn, TikTok, Microsoft budget/bidding + cross-platform allocationaudit-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 ( 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 estimatedfixtime < 15 minutes THEN flag as Quick Win SORT BY (severitymultiplier x estimatedimpact) DESC
## Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- **Author:** [Maxymize](https://github.com/Maxymize)
- **Source:** [Maxymize/maxym-ai-ads](https://github.com/Maxymize/maxym-ai-ads)
- **License:** MIT
- **Homepage:** https://github.com/Maxymize/maxym-ai-ads/blob/main/docs/BLUEPRINT-ZERO-TO-SALES.md
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.