analytics-tracking

Name: analytics-tracking
Availability: InStock
Author: boraperusic

Design and validate analytics tracking systems for decision-ready measurement signals.

Updated Apr 12, 2026

Search Tags:#analytics #validation #governance #measurement #attribution #data-quality #event-design

Ready to run

npx skills add https://github.com/BoraPerusic/agents --skill analytics-tracking-boraperusic

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: analytics-tracking
Source: https://github.com/BoraPerusic/agents/tree/main/skills/to%20try/antigravity-bundle-data-analytics/skills/analytics-tracking
Command: npx skills add https://github.com/BoraPerusic/agents --skill analytics-tracking-boraperusic

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.

Core Features & Use Cases

Measurement Readiness & Signal Quality Index assessment
Event taxonomy design, naming conventions, data quality validation, and governance guidance
GA4/GTM guidance, UTM discipline, and validation workflows

Quick Start

Audit your current analytics setup and define a measurement readiness plan to produce trustworthy decision-ready signals.

Frequently Asked Questions about analytics-tracking

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

FAQPage Schema

What is a measurement readiness index for analytics tracking?▼

A measurement readiness index assesses your analytics tracking setup to ensure it produces reliable, decision-ready signals. It evaluates event design, data quality, and governance to determine if your measurement system is ready for trustworthy analysis.

How do I design a reliable analytics tracking plan for GA4 and GTM?▼

Design reliable analytics tracking by creating a structured tracking plan with event taxonomy, naming conventions, and validation workflows. The plan includes conversion rules, implementation notes, and governance guidance for GA4 and GTM setups.

How do I validate data quality and attribution in my analytics setup?▼

Validate data quality and attribution by applying structured validation steps and conversion rules to your tracking system. This process audits event design and governance to ensure your analytics produce decision-ready, trustworthy signals.

Can I use this analytics tracking approach for product and growth contexts?▼

Yes, this analytics tracking approach applies to marketing, product, and growth contexts. It covers measurement readiness, event design, conversions, attribution, and governance to produce decision-ready signals across these domains.

What's the best way to audit an existing analytics tracking system?▼

The best way to audit an analytics tracking system is assessing its measurement readiness index, reviewing event taxonomy and naming conventions, and running validation workflows. This identifies gaps in data quality and governance to produce reliable signals.

Why does my analytics data quality fail without event taxonomy and UTM discipline?▼

Analytics data quality fails without event taxonomy and UTM discipline because inconsistent naming and tracking create unreliable, fragmented signals. Structured governance, validation steps, and conversion rules are required to produce decision-ready data.