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validate-comprehensibility

Simulate student profiles to score editorial content legibility and cognitive load.

Updated Mar 21, 2026
Search Tags:#readability#engagement#cognitive-load#comprehensibility#student-simulator#education-accessibility#dua
One-click install
npx skills add https://github.com/JaviMontano/prolipa-plugins --skill validate-comprehensibility
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: validate-comprehensibility
Source: https://github.com/JaviMontano/prolipa-plugins/tree/main/scriba/skills/validate-comprehensibility
Command: npx skills add https://github.com/JaviMontano/prolipa-plugins --skill validate-comprehensibility

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Validate content comprehensibility across target student profiles by applying calibrated Student Simulator prompt-personas (AR, PR, NEE) to real editorial content, surfacing readability and cognitive load issues before human review.

Core Features & Use Cases

  • Simulate reading with three profiles (alto rendimiento, promedio, necesidades especiales) to evaluate legibility, cognitive load, and engagement per section.
  • Flag problematic fragments with section and paragraph precision, severity levels, and concrete simplification suggestions.
  • Generate a unified YAML report including a global score, per-section scores, per-profile scores, and actionable remediation guidance.

Quick Start

Run the validate-comprehensibility unit against your generated editorial content and inspect output/reporte-comprensibilidad-<UNIT-ID>.yaml.

Frequently Asked Questions about validate-comprehensibility

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

FAQPage Schema
How do I check content comprehensibility for different student profiles?▼

To check content comprehensibility, apply calibrated student simulator personas representing alto rendimiento, promedio, and necesidades especiales profiles to evaluate readability, cognitive load, and engagement across content sections.

What is the best way to measure cognitive load and readability in educational content?▼

Measuring cognitive load and readability involves simulating reading across multiple student profiles to compute per-section scores, flag problematic fragments by severity, and generate concrete simplification suggestions.

How do I generate a comprehensibility report with actionable simplification suggestions?▼

Generate a comprehensibility report by running the validation unit against editorial content to produce a YAML file containing global scores, per-section evaluations, flagged fragments, and threshold-based decisions.

Can I evaluate engagement and readability for special needs students automatically?▼

Yes, you can evaluate engagement and readability for special needs students by applying the Necesidades Educativas Especiales (NEE) simulator profile, which assesses cognitive load and legibilidad tailored to accessibility requirements.

How does the student simulator evaluate content sections like apertura and desarrollo?▼

The student simulator evaluates content sections by applying three prompt-personas to simulate reading apertura, desarrollo, cierre, and evaluacion, computing individual scores for legibilidad, carga cognitiva, and enganche per section.

What are the limitations of using automated readability scoring for editorial content?▼

Automated readability scoring relies on calibrated simulator personas and threshold rules to flag fragments, meaning results depend on the accuracy of the simulated profiles and may not capture all nuanced human comprehension issues.

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