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tree-testing

Analyzes tree-testing results to quantify UX metrics and outputs structured findings with source references and recommendations.

13|4|Updated Mar 14, 2026
Search Tags:#insights#recommendations#analyze#ux-research#tree-testing#findability#path-analysis
One-click install
npx skills add https://github.com/henrique-simoes/Istara --skill tree-testing-henrique-simoes
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tree-testing
Source: https://github.com/henrique-simoes/Istara/tree/main/skills/develop/tree-testing
Command: npx skills add https://github.com/henrique-simoes/Istara --skill tree-testing-henrique-simoes

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Tree-testing results are often scattered and hard to interpret. This Skill consolidates analysis to produce standardized scores for findability, success, and path effectiveness, enabling faster, evidence-based IA improvements.

Core Features & Use Cases

  • Compute findability and path-directness scores from tree-testing data.
  • Generate structured insights with source references and prioritized recommendations.
  • Use cases include evaluating navigation IA, identifying drop-off points, and guiding redesign decisions.

Quick Start

Process your tree-testing data by running the skill with your project files and context to generate a complete analysis report.

Frequently Asked Questions about tree-testing

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

FAQPage Schema
How do I analyze tree-testing data to measure findability and path directness?▼

Tree-testing analysis quantifies findability and path directness by processing project files like PDF, CSV, and DOCX to compute task success rates and generate structured UX insights with source references.

What is the best way to turn UX tree-testing results into actionable recommendations?▼

The best way to turn tree-testing results into actionable recommendations is to consolidate raw data into standardized scores for findability and success, enabling evidence-based information architecture improvements.

Can I use CSV and PDF files to evaluate navigation IA drop-off points?▼

Yes, you can process CSV and PDF files along with project context to evaluate navigation IA, identify user drop-off points, and guide redesign decisions with prioritized insights.

Does tree-testing analysis require specific data formats to calculate task success rates?▼

Tree-testing analysis supports multiple data formats including PDF, DOCX, TXT, CSV, and MD, allowing you to calculate task success rates and path effectiveness without needing a single standardized format.

How do tree-testing path analysis scores help guide information architecture redesign?▼

Tree-testing path analysis scores highlight where users struggle to find content, providing evidence-based metrics that directly guide information architecture redesign decisions and improve overall hierarchy structures.

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