# How to Use Image Generation Skills with ChatGPT Images in Taste Skill

> Learn to generate high-fidelity UI mockups in ChatGPT using Taste Skill's image generation. Install the skills and follow structured output rules for powerful design capabilities.

- Repository: [Leon Lin/taste-skill](https://github.com/Leonxlnx/taste-skill)
- Tags: how-to-guide
- Published: 2026-06-06

---

**You can generate high-fidelity UI mockups in ChatGPT by installing Taste Skill's image generation skills via `npx skills add` and prompting the model to follow the structured output rules defined in each skill's [`SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/SKILL.md) file.**

The Leonxlnx/taste-skill repository ships specialized **image generation skills** that integrate directly with ChatGPT's native image capabilities. These skills are pure data files stored in the `skills/` directory that the Agent-Skills CLI discovers and loads into any compatible LLM agent. By leveraging these definitions, you can convert text prompts into implementation-ready design references without manual art direction.

## Installing an Image Generation Skill

To add an image generation skill to your environment, use the `npx skills add` command followed by the repository URL and the specific skill name. The CLI scans the `skills/` folder and registers each skill by its `name:` front-matter.

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

```

This command invokes the [`skill.sh`](https://github.com/Leonxlnx/taste-skill/blob/main/skill.sh) helper script, which forwards the `--skill` flag to the underlying agent-skills runtime. According to the repository's [`README.md`](https://github.com/Leonxlnx/taste-skill/blob/main/README.md) (lines 46-57), this workflow supports any LLM agent that parses the Agent-Skills format, including ChatGPT's image generation mode.

## Available Image Generation Skills

Taste Skill provides three primary image generation skills located in the `skills/` directory:

- **`imagegen-frontend-web`** – Generates website compositions including hero sections and landing page layouts. Defined in [`skills/imagegen-frontend-web/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/imagegen-frontend-web/SKILL.md) (lines 1-5).

- **`imagegen-frontend-mobile`** – Produces mobile-screen UI comps for iOS and Android interfaces. Defined in [`skills/imagegen-frontend-mobile/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/imagegen-frontend-mobile/SKILL.md).

- **`brandkit`** – Creates brand identity boards containing logos, color palettes, and typography systems. Defined in [`skills/brandkit/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/brandkit/SKILL.md).

Each skill contains hard output rules and art-direction guidelines that constrain the model's generation behavior.

## Prompting ChatGPT with Image Generation Skills

When ChatGPT has image generation enabled, invoke the skill by name in your prompt. The model will follow the internal rules specified in the skill's definition.

```markdown
User:
> **Please use the `imagegen-frontend-web` skill** to create an 8-section landing page for a SaaS product called "FinTrack" with a clean, data-driven aesthetic and deep-dark palette.

```

The [`skills/imagegen-frontend-web/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/imagegen-frontend-web/SKILL.md) file automatically enforces several constraints:

- **One horizontal image per section** – The PRIMARY OUTPUT RULE (lines 99-107) mandates that the model output exactly one image for each requested section, labeled as "Section X of N".

- **Varied composition anchors** – The skill instructs the model to avoid default left-text/right-image layouts, instead cycling through top-center, diagonal, and full-bleed compositions (lines 25-42).

- **Premium art direction** – Constraints include palette consistency, conversion-focused layouts, and cinematic lighting specifications (lines 44-66).

If the model can only render one image per turn, the skill's sequential output clause (lines 19-20) directs ChatGPT to emit multiple images in the same textual response, which ChatGPT Images renders sequentially.

## Chaining Images to Code Generation

After generating visual frames, you can feed them into the `image-to-code` skill to produce implementation files.

```bash
npx skills add https://github.com/Leonxlnx/taste-skill --skill "image-to-code"

```

Structure your prompt as a two-step pipeline: first request the images using `imagegen-frontend-web`, then instruct the model to **run the `image-to-code` skill** on the resulting frames to emit HTML, GSAP, or React components. This bridges design and development without context switching.

## Key Files and Architecture

| File | Description |
|------|-------------|
| [`skill.sh`](https://github.com/Leonxlnx/taste-skill/blob/main/skill.sh) | CLI wrapper that forwards skill selection to the agent-skills runtime. |
| [`README.md`](https://github.com/Leonxlnx/taste-skill/blob/main/README.md) | Documents installation commands and lists available image-generation skills (lines 46-57). |
| [`skills/imagegen-frontend-web/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/imagegen-frontend-web/SKILL.md) | Full specification of web image generation, including output rules and composition guidelines. |
| [`skills/imagegen-frontend-mobile/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/imagegen-frontend-mobile/SKILL.md) | Mobile-specific image generation rules and viewport constraints. |
| [`skills/brandkit/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/brandkit/SKILL.md) | Brand identity generation protocols for logos and color systems. |
| [`skills/image-to-code-skill/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/image-to-code-skill/SKILL.md) | Optional follow-up skill for converting generated images into frontend code. |

## Summary

- Install image generation skills using `npx skills add https://github.com/Leonxlnx/taste-skill --skill "<name>"`.
- Available skills include `imagegen-frontend-web`, `imagegen-frontend-mobile`, and `brandkit`.
- Each skill enforces strict output rules via its [`SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/SKILL.md) definition, guaranteeing one horizontal image per section and varied compositions.
- ChatGPT Images can render these sequentially in a single conversation turn.
- Chain the `image-to-code` skill to transform generated mockups into implementation-ready code.

## Frequently Asked Questions

### What is the Taste Skill repository?

Taste Skill is an open-source collection of Agent-Skills format files hosted by Leonxlnx. It provides specialized [`SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/SKILL.md) definitions that standardize how LLMs generate specific outputs, including UI mockups, brand assets, and frontend code. Each skill resides in the `skills/` directory and is discoverable by the `npx skills` CLI.

### How does the `imagegen-frontend-web` skill enforce output consistency?

The skill defines hard constraints in [`skills/imagegen-frontend-web/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/skills/imagegen-frontend-web/SKILL.md). The PRIMARY OUTPUT RULE (lines 99-107) mandates exactly one horizontal image per section, while composition guidelines (lines 25-42) prevent repetitive layouts by requiring varied anchoring strategies. These rules are embedded in the skill's system prompt, constraining the model's generation parameters.

### Can I use these skills with models other than ChatGPT?

Yes. The Agent-Skills format is model-agnostic. Any LLM agent that supports the specification—including Claude, Cursor, and local agents—can load the [`SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/SKILL.md) files from the Leonxlnx/taste-skill repository. However, the sequential image generation workflow is specifically optimized for ChatGPT's native image generation mode.

### How do I convert generated images into code?

First generate the visual frames using `imagegen-frontend-web` or `imagegen-frontend-mobile`. Then install the `image-to-code` skill and prompt the model to analyze the generated images using that skill's protocol. This process reads the visual layout and emits corresponding HTML, CSS, or framework-specific components based on the [`image-to-code-skill/SKILL.md`](https://github.com/Leonxlnx/taste-skill/blob/main/image-to-code-skill/SKILL.md) specifications.