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imagegen

Generate and edit digital images using the OpenAI Python SDK.

28|Updated Jan 3, 2026
Search Tags:#image generation#asset creation#image editing#batch processing#inpainting#prompt augmentation#openai api
One-click install
npx skills add https://github.com/ma08/botfiles --skill imagegen-ma08
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: imagegen
Source: https://github.com/ma08/botfiles/tree/main/codex/skills/imagegen
Command: npx skills add https://github.com/ma08/botfiles --skill imagegen-ma08

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai, pillow, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill eliminates the need for manual design tooling when creating or modifying digital images for projects like websites, product listings, game assets, and marketing materials, using OpenAI's Image API to produce high-quality results in minutes.

Core Features & Use Cases

  • Image Generation: Create new assets including product mockups, UI mockups, concept art, logos, infographics, and photorealistic scenes using structured, production-ready prompts.
  • Image Editing: Modify existing images via inpainting, background replacement, object removal, text localization, and style transfer while preserving key invariants like subject identity and layout.
  • Batch Processing: Run multiple image generation or edit jobs concurrently from a JSONL file to create bulk asset sets with consistent styling and constraints. For example, if you need 10 product mockups for an e-commerce store with identical lighting and background, this skill can generate them all at once with a single batch run.

Quick Start

Ask the AI to generate a minimal hero image of a ceramic coffee mug for your landing page, and it will automatically run the bundled CLI to produce the final optimized asset with the correct prompt and settings.

Frequently Asked Questions about imagegen

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

FAQPage Schema
How do I generate product mockups and concept art using the OpenAI Image API?▼

Generate product mockups and concept art by running the bundled CLI with structured, production-ready prompts via the OpenAI Image API. This process produces high-quality digital assets for web, product, and creative projects without requiring manual design tooling.

Can I use Python to batch process image generation jobs from a JSONL file?▼

Batch process image generation jobs by running multiple tasks concurrently from a JSONL file using Python. This approach creates bulk asset sets with consistent styling and constraints, such as generating multiple e-commerce product mockups with identical lighting in a single run.

How does inpainting work for background replacement and object removal in images?▼

Inpainting modifies existing images by replacing backgrounds, removing objects, and localizing text. This image editing technique preserves key invariants like subject identity and layout during background replacement and style transfer operations.

Do I need an OPENAI_API_KEY environment variable to run image generation scripts?▼

You need the OPENAI_API_KEY environment variable and the OpenAI Python SDK to run image generation scripts. The bundled CLI uses these dependencies for deterministic, reproducible runs with structured prompt augmentation and retry logic for transient API errors.

What is the best way to automate text localization for digital image assets?▼

Automate text localization by using the bundled CLI to apply image editing functions via the OpenAI Image API. This method handles text localization while preserving key invariants like subject identity and layout for consistent asset creation.

Why does image generation fail with transient OpenAI API errors during batch processing?▼

Transient OpenAI API errors occur during batch processing due to temporary network or service issues. The bundled CLI includes retry logic to automatically handle these transient API errors, ensuring deterministic and reproducible image generation runs.

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