universal-learner

Extracts reusable elements from prompts across multiple domains into a shared library.

1.4k|212|Updated Jan 5, 2026
One-click install
npx skills add https://github.com/huangserva/skill-prompt-generator --skill universal-learner
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: universal-learner
Source: https://github.com/huangserva/skill-prompt-generator/tree/main/.claude/skills/universal-learner
Command: npx skills add https://github.com/huangserva/skill-prompt-generator --skill universal-learner

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automatically extracts reusable elements from prompts, building a growing Universal Elements Library for cross-domain prompts.

Core Features & Use Cases

  • Auto-extract: from any prompt to reusable elements for future prompts.
  • Multi-domain support: covers portrait, interior, product, design, art, video, and common photography.
  • Learning & curation: accumulates knowledge with semi-automatic review and reporting.

Quick Start

Use the universal-learner to ingest a prompt and save derived elements to the library, then generate a learning report.

Frequently Asked Questions about universal-learner

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

FAQPage Schema
How do I extract reusable elements from prompts to build a cross-domain knowledge library?▼

Extracting reusable elements from prompts involves automated domain recognition, element tagging, and reusability scoring to catalog cross-domain knowledge for portrait, interior, product, and design prompts.

What is a cross-domain prompt analysis pipeline for scalable learning?▼

A cross-domain prompt analysis pipeline automates element extraction and database updating, enabling semi-automatic review and reporting to accumulate scalable learning across art, video, and photography domains.

Does automated prompt element extraction work for both photography and interior design prompts?▼

Automated prompt element extraction works across portrait, interior, product, design, art, video, and common photography prompts, applying universal recognition to tag and catalog reusable elements.

How do I score prompt reusability and update my knowledge database automatically?▼

Scoring prompt reusability and updating a knowledge database is achieved through an automated learning pipeline that ingests prompts, extracts elements, applies tagging, and updates the library.

What are the limitations of semi-automatic prompt cataloging for multi-domain knowledge?▼

Semi-automatic prompt cataloging requires manual review for extracted elements, meaning reusability scoring and database updating are not fully autonomous and need human curation to maintain knowledge library quality.

Can I use universal-learner to generate a learning report from accumulated prompt elements?▼

Universal-learner generates a learning report by ingesting prompts, extracting and tagging reusable elements, and saving derived elements to the library, satisfying domain recognition and reusability scoring.