OpenViSTAI · Agents · Blockchain · Crypto
Submit a project
Menu
Image & Video AI

AI Visual Prompt Cookbook

AI Visual Prompt Cookbook is a collection of reusable visual-style prompts stored as JSON files, with templates and variables for adapting image-generation prompts to different subjects and projects.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

AI Visual Prompt Cookbook — OpenViST project profile in Image & Video AI.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when you want a reusable visual style framework to adapt for an image prompt, rather than composing every style instruction as a one-off text prompt.

Who it is for

  • Designers and image creators seeking reusable visual directions for related images.
  • People who want structured prompt examples for posters, product campaigns, editorial layouts, travel visuals or collage.

Documented uses

  • Browse visual styles by category and select a starting point.
  • Copy a style JSON and replace its variables with project-specific content.
  • Use a structured style reference to build prompts for an image-generation workflow.
Before you choose

Requirements & limits

  • Prompts are supplied as style.json files with variables that users fill or edit.
  • The repository describes the files as inputs to an external image-capable model or workflow; it is not itself the image generator.
  • The README recommends multimodal image models that can process long structured prompts.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Adapt a JSON style for an image prompt

Prepare a selected visual-style prompt with project-specific values and send it to an image model.

Before you start

  • A style folder from the cookbook containing a style.json file.
  • An image-capable workflow that accepts long structured JSON prompts.

Steps

  1. Browse the featured styles, quick links or all-styles gallery and choose a style.

  2. Open its folder and copy style.json.

  3. Replace the declared environment_variables with your values, or edit a case in examples[*].values.

  4. Paste the completed JSON into an image workflow, generate the final image prompt, and send it to your image model.

Expected outcome

A project-specific prompt using the selected style's visual direction and variables.

Guide limitations

  • The README says the workflow works best with end-to-end multimodal image models that can read long structured prompts; other multimodal systems may also work.
  • The project description does not independently test model-specific consistency, so the JSON format should not be taken as a guarantee of identical outputs.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
13 October 2026
Original website title
VigoZhao/AI-Visual-Prompt-Cookbook · Official homepage title · retained in its source language
How we review sourcesSuggest a correction