Web Imagegen Prompting Skill for Codex

Prompt generated imagery for premium websites. Use when Codex needs hero images, product scenes, editorial visuals, backgrounds, portraits, venue imagery, campaign art, texture assets, mockups, or image-generation direction for luxury, cinematic, Squarespace-polished, Viktor Oddy-adjacent, or non-generic site visuals.

2k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

115

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/TheGoat395/Codex-Skills --skill web-imagegen-prompting

What comes with it

4 644 bytes besides the instruction

agents/openai.yaml

references/web-imagegen-prompting-guide.md

The instruction itself

3 sections, as written by the author

Web Imagegen Prompting

Use this skill to make generated imagery usable as website media instead of vague atmospheric filler.

Workflow

Inspect the project, media assets, framework image/video APIs, responsive breakpoints, accessibility requirements, and verification commands.
Read Web Imagegen Prompting Guide for detailed direction before changing visuals or code.
Define the media's job: proof, desire, navigation, instruction, atmosphere, conversion, or accessibility.
Implement with stable dimensions, responsive crops, useful fallbacks, and real content hierarchy.
Inspect rendered desktop and mobile states, then refine crop, contrast, loading, labels, captions, and polish.

Always Protect

Inspect before coding: framework, image/video components, asset folders, CMS or source content, styling system, responsive breakpoints, performance checks, accessibility checks, and available browser QA commands.
Treat images and video as content strategy, not decoration: every asset should reveal the real product, person, venue, object, interface, proof, or mood needed by the page.
Avoid generic stock-like visuals, dark blurred filler, random gradients, and media that crops away the subject users need to inspect.
Plan desktop, mobile, high-density, slow-network, reduced-motion, no-autoplay, failed-asset, and screen-reader states.
Reserve layout space with dimensions, aspect-ratio, CSS constraints, or framework image components to avoid layout shift.
Use meaningful alt text for informative images, empty alt for decorative images, captions/transcripts/tracks for media that needs them, and visible text for critical information.
Before delivery, inspect rendered desktop and mobile media crops, verify assets load without 404s, and run available lint/build/test/browser checks.

Other skills for the same job

different authors, same section of the catalogue

Canvas Design

by anthropics

vendor ×13

Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.

Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.

Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.

Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.

13k tokens

How to use it

Copy the folder

Take thegoat395/web-imagegen-prompting from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.