How to Use Image-Generation Skills with ChatGPT Images: A Complete Guide to imagegen-frontend-web and brandkit

Copy the SKILL.md content from imagegen-frontend-web or brandkit into your ChatGPT Images prompt and reference the skill name to enforce strict visual rules like "one horizontal image per section" and palette discipline.

The taste-skill repository provides structured image-generation skills that turn ChatGPT Images into a premium design assistant. By loading the imagegen-frontend-web or brandkit SKILL.md files, you constrain the LLM with hard output rules that guarantee consistent, high-fidelity visual frames without manual iteration. These skills contain pure-text prompts that the LLM treats as system-level instructions, enabling deterministic output for web comps and brand assets.

Architecture Overview

The system relies on three core components working together to resolve skill names and enforce visual discipline.

Skill registry – The skill.sh file maintains a Bash map that resolves skill names to their corresponding instruction files. This registry enables the CLI to locate the correct SKILL.md when you run npx skills add.

Image-generation SKILL.md files – Located at skills/imagegen-frontend-web/SKILL.md and skills/brandkit/SKILL.md, these files contain pure-text prompts that define hard output rules (e.g., one horizontal image per section), visual DNA (hero composition bias, palette discipline), and exact prompt templates. Because they contain only natural-language directives with no executable code, ChatGPT Images can ingest them directly as behavioral constraints.

README documentation – The README.md documents the CLI workflow and explains how to discover and use these skills with any image-mode LLM.

Installation and Setup

While you can paste skill content directly into a chat, installing the skill register enables auto-discovery for agents that load skills from the filesystem.

npx skills add https://github.com/Leonxlnx/taste-skill --skill "imagegen-frontend-web"
npx skills add https://github.com/Leonxlnx/taste-skill --skill "brandkit"

The CLI reads skill.sh, maps the requested name to the correct SKILL.md, and copies it into your local skill store. This step is optional for ChatGPT Images but essential for agents that auto-load skills from disk.

Prompting Workflow

When ChatGPT Images receives a prompt containing a skill reference, it loads the corresponding SKILL.md and obeys its rules as system-level instructions. The workflow follows five distinct stages:

1. Skill injection – Either paste the full SKILL.md content or reference the skill by name.
2. Brief provision – Supply the variable design brief (target audience, mood, sections).
3. Rule enforcement – The LLM applies the skill's hard output rules (unchanging constraints).
4. Image generation – ChatGPT Images returns PNG or WebP frames following the strict visual DNA.
5. Downstream consumption – Feed the frames to image-to-code-skill or other tools for implementation.

Direct Paste Method

Copy the entire contents of skills/imagegen-frontend-web/SKILL.md or skills/brandkit/SKILL.md directly into the conversation. The LLM treats this as a system prompt that establishes visual constraints before you provide your design brief.

Reference by Name Method

Most image-aware agents recognize skill references using either XML-style tags or plain text patterns:

<skill>imagegen-frontend-web</skill>

Or:

follow skill: brandkit

The agent looks up the registered file via skill.sh or its internal registry and applies the rules automatically.

Practical Examples

Generating Landing Pages with imagegen-frontend-web

The imagegen-frontend-web skill enforces strict section counting and horizontal image requirements. According to lines 6-22 of its SKILL.md, it mandates one horizontal image per section with specific labeling conventions.

<skill>imagegen-frontend-web</skill>

Create a premium landing page for a fintech startup called "VaultPay".
- Target audience: small-business owners
- Desired mood: trustworthy, modern, slightly bold
- Sections: hero, trust bar, features, product showcase, testimonial, pricing, CTA

Please follow the hard output rule: one horizontal image per section, labeled "Section X of 7: <name>".
Use a deep-dark palette with cyan accents and a giant-statement hero.

The LLM reads the hard output rule from the skill file and returns seven separate horizontal images, each prefixed with the requested label and following the hero composition bias specified in the skill's visual DNA.

Building Brand Kits with brandkit

The brandkit skill defines a default 3×3 layout (lines 73-80 of SKILL.md) and specific visual modes for generating comprehensive brand boards.

<skill>brandkit</skill>

Design a brand-kit overview for "NebulaAI", an AI-assistant platform.
- Category: voice / communication
- Core metaphor: waveform + orbital path
- Desired visual mode: dark developer / builder

Use the default 3×3 layout, dark charcoal canvas, and a cyan-orange accent palette.

The LLM follows the prompt template defined in lines 36-44 of the skill file, outputting a single 4:3 board containing logo variations, construction grids, digital mockups, color systems, and typography specimens.

Chaining to Code Generation

You can chain image-generation skills with image-to-code-skill to move from visual concept to implementation:

follow skill: imagegen-frontend-web

Generate a 6-section website for "EcoTravel", a sustainable travel app.

--- then ---

follow skill: image-to-code

Analyze the images you just produced and output clean HTML/CSS/React components.

The first block produces reference frames following the imagegen-frontend-web constraints; the second block triggers the downstream skill to parse those frames and emit implementation code.

Key Configuration Files

Keep these source files accessible when working with image-generation skills:

• skill.sh – The Bash registry that maps skill names to instruction files for CLI resolution.
• skills/imagegen-frontend-web/SKILL.md – Contains hard rules, composition biases, and section-count logic for web comps.
• skills/brandkit/SKILL.md – Defines brand-kit board structure, visual modes, and layout templates.
• README.md – Central documentation covering installation commands and ChatGPT Images integration tips.
• skills/image-to-code-skill/SKILL.md – Optional pipeline component for converting generated images to code.

Summary

• Image-generation skills are pure-text prompt files that constrain ChatGPT Images with hard output rules and visual DNA.
• Installation via npx skills add is optional for ChatGPT Images but required for filesystem-based agents.
• Activation works by either pasting the full SKILL.md content or referencing the skill name (imagegen-frontend-web or brandkit) in your prompt.
• Consistency is guaranteed through immutable rules like "one horizontal image per section" for web comps or "3×3 layout" for brand kits.
• Chaining skills allows you to generate visual frames and immediately convert them to HTML, CSS, or React components using image-to-code-skill.

Frequently Asked Questions

Do I need to install anything to use these skills with ChatGPT Images?

No installation is required for ChatGPT Images. You can copy the entire contents of skills/imagegen-frontend-web/SKILL.md or skills/brandkit/SKILL.md directly into your conversation. However, running npx skills add registers the skill in your local filesystem, which is necessary if you are using agents that auto-load skills from disk rather than accepting pasted instructions.

What is the difference between imagegen-frontend-web and brandkit?

imagegen-frontend-web is optimized for multi-section website wireframes and enforces rules like "one horizontal image per section" with strict section counting (lines 6-22 of its SKILL.md). brandkit generates single-board brand identity overviews using a default 3×3 layout (lines 73-80) and focuses on logo systems, color palettes, and typography grids. Choose the former for page-level UI and the latter for identity systems.

Can I modify the hard output rules in the SKILL.md files?

Yes, because the skills are open-source text files hosted in the Leonxlnx/taste-skill repository. You can fork the repository and edit the hard output rules in skills/imagegen-frontend-web/SKILL.md or skills/brandkit/SKILL.md to customize section counts, aspect ratios, or palette constraints. Your modified skill can then be loaded via npx skills add using your fork's URL.

How do I convert the generated images into actual code?

After generating images with imagegen-frontend-web, reference the image-to-code-skill in a follow-up prompt. This skill (located at skills/image-to-code-skill/SKILL.md) instructs the LLM to analyze the visual frames and output clean HTML, CSS, or React components that replicate the design, effectively bridging the gap between visual concept and implementation.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}