analytics-tracking

Track anonymized page views, feature usage, and errors for SuperTool.

2|Updated Oct 24, 2025

Search Tags:#analytics #privacy #tracking #event #anonymized #tool-usage

Ready to run

npx skills add https://github.com/ferryhinardi/supertool --skill analytics-tracking-ferryhinardi

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: analytics-tracking
Source: https://github.com/ferryhinardi/supertool/tree/main/.github/skills/analytics-tracking
Command: npx skills add https://github.com/ferryhinardi/supertool --skill analytics-tracking-ferryhinardi

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables privacy-centric analytics tracking to monitor SuperTool usage while avoiding PII exposure and sensitive data leaks.

Core Features & Use Cases

Anonymized event tracking for tool usage, feature interactions, and errors.
Performance metrics collection (timing) and usage frequency across tools.
Use Case: Monitor which features get used most to inform future improvements without capturing user identifiers.

Quick Start

Start by importing the analytics module and triggering a page_view on tool load. Example: trackToolEvent('tool-id', 'page_view', {})

Frequently Asked Questions about analytics-tracking

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

FAQPage Schema

How do I track tool usage analytics without collecting personally identifiable information?▼

You can track tool usage analytics without collecting PII by using a privacy-first tracking module that captures page views, feature interactions, and errors in an anonymized form. This ensures no user identifiers are recorded.

How do I implement anonymized event tracking for feature usage and errors?▼

Implement anonymized event tracking by triggering events with snake_case names, passing empty or sanitized metadata objects, and ensuring no credentials or PII are included in the tracking calls for feature usage and errors.

What is the best way to monitor feature usage frequency and performance metrics without exposing user data?▼

The best way to monitor feature usage frequency and performance metrics safely is to aggregate timing data and usage events anonymously, preventing any sensitive user data from leaving the tool environment.

Does privacy-first analytics tracking require specific naming conventions for events?▼

Yes, privacy-first analytics tracking enforces snake_case naming conventions for events and requires anonymized metadata to maintain strict data privacy standards across all tracked interactions.

Can I capture page views and performance timing across all tools automatically?▼

You can capture page views and performance timing across all tools by applying the analytics tracking module globally, triggering a page_view event upon tool load to monitor usage consistently.

Why should I use anonymized metadata instead of standard user identifiers in tracking calls?▼

Using anonymized metadata instead of standard user identifiers prevents PII exposure and sensitive data leaks, allowing you to inform future improvements without compromising user privacy.