How is the data stored and accessed?

Extracted elements are saved to a structured SQLite database (elements.db) and a JSON export, making the library easy to query or migrate.

What is the reusability score?

It is a 1-10 rating assigned to each extracted element based on its clarity, independence, and how easily it can be applied to different contexts.

What domains does Universal Learner support?

It currently supports seven specialized domains: portrait photography, interior design, product shots, graphic design, art styles, video generation, and common photography techniques.

Can it learn from complex design frameworks?

Yes, it includes a 'Module System' mode specifically designed to identify hierarchical structures, preserving full design specifications and visual references.

Is the learning process manual or automatic?

The skill operates in a semi-automatic mode, generating a comprehensive report for user review to ensure that only high-quality data enters the permanent database.

Universal Learner

Name: Universal Learner
Author: tianzecn

bytianzecn

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Productivity & Workflow

Extracts reusable elements and modular patterns from creative prompts to build a persistent, cross-domain knowledge library.

Universal Learner is a specialized capability designed to deconstruct complex prompts and design specifications into structured, reusable components. By analyzing inputs across seven distinct domains—including photography, interior design, and UI systems—it automatically identifies techniques, materials, and layouts, storing them in a centralized SQLite database. The skill goes beyond simple parsing by calculating reusability scores and preserving entire design frameworks as visual references, allowing users to transform one-off prompt engineering efforts into a permanent, searchable asset library for future projects.

Key Features

011 GitHub stars

02Detailed learning reports with element-by-element quality assessment

03Design system preservation for complex workflows and style guides

04Automated element extraction with SQLite and JSON database integration

05Smart tagging and reusability scoring for quality control

06Multi-domain classification for photography, design, art, and video

Use Cases

01Archiving and modularizing complex design systems for consistent project branding

02Converting successful workflow descriptions into reusable implementation patterns

03Building a structured library of high-performing prompt components for AI image generation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add tianzecn/myclaudecode universal-learner

For use in Claude.ai and ChatGPT

Download Skill