avikmaj

Universal Master Art Library Kit — AI skill for Claude Code

AI community

A Markdown-first, model-neutral image-context and prompt-engineering library.

How to install Universal Master Art Library Kit

This entry records only its repository, not the path inside it, so there is no exact command to give. Open avikmaj/Universal-Master-Art-Library-Kit and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Universal Master Art Library Kit does

A Markdown-first, model-neutral image-context and prompt-engineering library. This repository is designed for use with ChatGPT, Grok, Claude, Midjourney, Flux, SDXL, ComfyUI, and other image-generation workflows.

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README

# Universal Master Art Library Kit

A Markdown-first, model-neutral image-context and prompt-engineering library.

This repository is designed for use with ChatGPT, Grok, Claude, Midjourney, Flux, SDXL, ComfyUI, and other image-generation workflows.

Design principles

  • One Markdown file per reusable visual context, not one file per isolated prompt.
  • Separate image sector knowledge from model-specific prompt syntax.
  • Use GitHub as the read-only source of truth.
  • Preserve reusable context: purpose, audience, composition, lighting, style, constraints, reference-image rules, and quality checks.
  • Add model adapters only at the final prompt-conversion stage.

Start here

  1. Read INDEX.md.
  2. Select the appropriate sector file.
  3. Read the relevant files in 00-core/.
  4. Apply a model adapter from 12-model-adapters/.
  5. Use 13-quality-safety/ to review the final prompt and image.

Project layout

  • 00-core/ — universal image-prompt foundations
  • 01-people-portraits/ through 10-art-styles-media/ — sector context libraries
  • 11-editing-reference/ — image editing and reference-image workflows
  • 12-model-adapters/ — ChatGPT, Grok, Claude, and other platform adaptations
  • 13-quality-safety/ — quality, safety, rights, and accessibility checks
  • _templates/ — repeatable Markdown authoring templates
  • examples/ — end-to-end production examples