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pixel-audit

Diagnose Meta and Google pixel implementation and 1st Party data quality.

267|63|Updated Feb 15, 2026
Search Tags:#data quality#tracking#campaign#pixel#lookalike#ad diagnostics
One-click install
npx skills add https://github.com/modu-ai/cowork-plugins --skill pixel-audit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pixel-audit
Source: https://github.com/modu-ai/cowork-plugins/tree/main/moai-marketing/skills/pixel-audit
Command: npx skills add https://github.com/modu-ai/cowork-plugins --skill pixel-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill identifies and diagnoses issues related to pixel implementation and the utilization of 1st Party data, enabling advertisers to improve ad targeting and attribution accuracy.

Core Features & Use Cases

  • Pixel Verification: Checks proper installation of Meta and Google pixels, including event tracking and parameter setup.
  • Data Quality Assessment: Evaluates the completeness and effectiveness of 1st Party data collection such as emails, phone numbers, and CRM data.
  • Lookalike Audience Analysis: Assesses seed data quality for lookalike audiences, prioritizing VIP customer segments for better ad performance.
  • Use Case: A marketer wants to ensure their pixel setup is correct and their 1st Party data is leveraged effectively to target high-value customers with lookalike audiences.

Quick Start

Input your website URL along with details of your pixel and data usage, then review the generated diagnosis report to identify areas for immediate improvement.

Frequently Asked Questions about pixel-audit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check if my Facebook and Google pixel implementation is tracking events correctly?▼

To check pixel implementation, you need to verify proper installation of Meta and Google pixels, including event tracking and parameter setup. This process diagnoses pixel issues to improve ad targeting and attribution accuracy.

What is the best way to assess first party data quality for lookalike audiences?▼

Assessing first party data quality involves evaluating the completeness and effectiveness of collected emails, phone numbers, and CRM data. This analysis prioritizes VIP customer segments to enhance seed data for lookalike audiences.

Why does my ad campaign targeting feel inefficient despite having CRM and email data?▼

Ad campaign targeting becomes inefficient when CRM and email data quality is poor or pixel parameters are incorrect. Diagnosing data completeness and event tracking setup identifies gaps to improve targeting efficiency.

Can I use this pixel diagnostic process for both Meta and Google ad campaigns?▼

Yes, the pixel diagnostic process supports both Meta and Google ad campaigns. It verifies proper installation and event parameter correctness for both platforms to ensure tracking complies with advertising best practices.

How do I diagnose ad tracking issues to improve my data infrastructure robustness?▼

Diagnosing ad tracking issues requires reviewing pixel setup and first party data collection against advertising best practices. This diagnostic generates a report identifying immediate areas to enhance data infrastructure robustness.

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