Trace

Analyze session replay data to detect frustration signals and UX issues.

68|14|Updated Jan 7, 2026

Search Tags:#qualitative data #user behavior #session replay #UX analysis #frustration detection #persona segmentation

Ready to run

npx skills add https://github.com/simota/agent-skills --skill trace-simota

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Trace
Source: https://github.com/simota/agent-skills/tree/main/trace
Command: npx skills add https://github.com/simota/agent-skills --skill trace-simota

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you understand the "why" behind user actions by analyzing session replays and identifying patterns of frustration or confusion, turning raw data into actionable UX insights.

Core Features & Use Cases

Session Replay Analysis: Analyze click patterns, navigation, and scroll behavior.
Frustration Detection: Identify rage clicks, back loops, and other signals of user struggle.
Persona-Based Segmentation: Understand how different user groups interact with your product.
UX Problem Storytelling: Translate behavioral data into clear narratives about user pain points.
Use Case: A product manager notices a drop in conversion on the checkout page. They use the Trace skill to analyze session replays, identify that users are rage-clicking the payment button and getting stuck in back loops, leading to abandonment. Trace provides a report with evidence and suggests A/B testing a clearer button design.

Quick Start

Analyze user session data to find frustration signals and report on them.

Frequently Asked Questions about Trace

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

FAQPage Schema

How do I identify user frustration signals from session replay data?▼

Session replay analysis uncovers the why behind user actions by tracking click patterns, scroll behavior, and navigation flows. It translates raw interaction data into actionable UX insights and narrative reports.

Can I segment UX analysis by different user personas?▼

Yes, UX analysis can be segmented by persona. This requires access to persona definitions alongside session replay logs to understand how different user groups interact with your product and validate hypotheses.

How do I turn qualitative data into UX problem storytelling reports?▼

Qualitative data is translated into UX problem storytelling by analyzing session replays for frustration signals and persona segmentation. This generates narrative reports detailing user pain points and behavioral patterns.

What do I need to analyze user behavior and validate product hypotheses?▼

To analyze user behavior and validate hypotheses, you need access to session replay logs and persona definitions. This allows you to identify behavioral patterns and frustration signals, turning raw data into actionable UX insights.

What are the limitations of using rage clicks and back loops for frustration detection?▼

Frustration detection using rage clicks and back loops identifies user struggle but relies entirely on access to comprehensive session replay logs. Without persona definitions, behavioral data lacks sufficient context for UX analysis.