ai-drawing-prompt

Translate image briefs into structured prompt packs for multiple image generation providers.

Updated Feb 21, 2026
One-click install
npx skills add https://github.com/leeyuyun/agent_skills --skill ai-drawing-prompt
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ai-drawing-prompt
Source: https://github.com/leeyuyun/agent_skills/tree/main/ai-drawing-prompt
Command: npx skills add https://github.com/leeyuyun/agent_skills --skill ai-drawing-prompt

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Turn informal image briefs into production-ready prompt packs that are deterministic, model-aligned, and safe to run across providers.

Core Features & Use Cases

  • Build a complete prompt package including Primary prompt, Parameter block, Negative/Avoidance block, Reference image block, Variants, and Iteration plan.
  • Map prompts to multiple providers (OpenAI GPT Image, Midjourney, SDXL, FLUX) with provider-specific constraints and safety guidance.
  • Leverage reference guidance files (references/model_profiles.md, references/safety_and_negative_guidance.md) to drive robust, repeatable prompts.

Quick Start

Provide your image brief and target model, and the AI Drawing Prompt skill will generate a complete prompt pack ready for execution.

Frequently Asked Questions about ai-drawing-prompt

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

FAQPage Schema
How do I generate production-ready AI image prompts from a simple brief?

To generate production-ready AI image prompts, provide an informal image brief and target model. The system translates the brief into a deterministic, model-aligned prompt pack including primary text, parameter controls, exclusions, and variants.

Can I use the same image prompt for Midjourney, SDXL, and FLUX?

You can target multiple providers like Midjourney, SDXL, and FLUX by mapping prompts with provider-specific constraints. The system enforces these constraints and requires reference guidance to ensure robust, repeatable outputs across different models.

What is a negative prompt block and why do I need it for image generation?

A negative or avoidance block defines elements to exclude from generated images. It enforces safety guidance and provider-specific constraints, preventing unwanted concepts, styles, or artifacts from appearing in the final output.

How do reference images improve AI prompt iteration?

Reference images drive robust, repeatable prompts by guiding concept, style, and constraint iterations. Leveraging reference guidance files ensures the generated prompt pack accurately aligns with the desired visual direction and model parameters.

Does this prompt generation method support safety constraints for AI models?

The method supports safety constraints by mapping prompts to provider-specific safety guidance. It utilizes dedicated reference files to enforce avoidance rules, ensuring generated image prompts remain safe and compliant across target providers.

What's the best way to structure model parameters for image generation prompts?

The best way to structure model parameters is to use a structured prompt package. This separates primary text, parameter controls, negative blocks, and variants, ensuring deterministic, model-aligned execution across providers.