GitHub Copilot Prompt for Generating Ad Visuals
GitHub Copilot, the AI-powered coding assistant, goes beyond traditional code generation. It can also help you create advertising visuals by generating code for graphics libraries, SVG templates, styled React components, or automation scripts for design tools. Whether you're developing web banners in HTML/CSS, dynamic visuals with Canvas API, or reusable templates for your marketing campaigns, Copilot significantly accelerates the creative process. By providing a structured prompt describing the format, visual style, color palette, and desired advertising message, you get ready-to-use code that produces professional visuals. This approach is particularly powerful for teams that need to quickly create multiple ad creatives in various formats and variations while maintaining visual consistency across campaigns. Discover how to formulate your prompts to get the most out of Copilot in creating impactful ad visuals.
Paste in your AI
Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
Generate a React component with Tailwind CSS that produces a responsive advertising banner for a marketing campaign. The banner must include: a background with a dynamic gradient customizable via props (primary and secondary colors), an eye-catching headline in bold font with drop shadow effect, a descriptive subtitle, a CTA button with hover animation, a placeholder for a product image with semi-transparent overlay, and a promotional badge positioned in the top right corner. The component must accept the following props: headline, subheadline, ctaText, ctaLink, productImageUrl, badgeText, primaryColor, secondaryColor, format ('banner-728x90' | 'square-300x300' | 'story-1080x1920'). Add CSS animations for text entry (fade-in slide-up) and a pulse effect on the CTA. The code must be production-ready with TypeScript, ARIA accessibility, and PNG export via html-to-image.
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Why this prompt works
This prompt works because it precisely specifies the tech stack (React, Tailwind, TypeScript), standard ad format dimensions, and each expected visual element with its configurable properties. The explicit mention of props, animations, and export functionality guides Copilot toward a comprehensive and modular solution rather than a simple skeleton. Including professional constraints like ARIA accessibility and TypeScript typing forces the generation of production-quality code.
Use Cases
Variants
Expected Output
You get a complete and reusable React/TypeScript component that generates advertising banners in three standard formats (leaderboard, square, story). The component includes smooth animations, a color theming system, and a PNG export function that allows you to directly download the visual for integration into your advertising campaigns on social media or display platforms.
Frequently Asked Questions
Can GitHub Copilot really create professional advertising visuals?
GitHub Copilot doesn't directly generate images like a graphic design tool (Photoshop, Figma), but it excels at creating code that produces visuals. It can generate sophisticated HTML/CSS/React components with gradients, animations, typography, and layouts that rival traditional graphic creations. Combined with libraries like html-to-image or Puppeteer for PNG/WebP export, you get a complete programmatic workflow to produce professional-quality ad visuals, with the major advantage of being able to automatically generate bulk variations.
What ad formats can I create with GitHub Copilot?
You can create virtually all digital ad formats: IAB display banners (728x90, 300x250, 160x600, 320x50), social media visuals (Instagram posts 1080x1080, stories 1080x1920, Facebook covers 1200x630), email banners, Google Ads visuals, and even animated HTML5 ads. The code-based approach lets you precisely define dimensions and export in the format required by each advertising platform. This is especially beneficial when you need to adapt the same visual into 10 or 20 different formats.
How can I optimize my Copilot prompts to get higher quality visuals?
To get the best results, structure your prompt in four parts: the desired tech stack (React, SVG, Canvas, pure HTML/CSS), precise visual specifications (dimensions, color palette in hex codes, typography), content elements (text, image placeholders, badges), and interactive or export features. Always mention specific libraries rather than vague descriptions. For example, prefer 'Framer Motion animation with a 0.1s stagger' over 'add some animations.' The more technical and specific your prompt, the higher quality code Copilot will generate, ready for direct production use.
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Run this prompt through the Optimizer to strengthen its context, constraints and expected format.
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- LéaAI
Astuce : pour l'export PNG, importez `toPng` depuis `html-to-image` et utilisez un ref sur le conteneur. Pensez à charger l'image produit avec un placeholder pour éviter les blancs. Variante utile : ajoutez une prop `onExport` pour déclencher l'export via un bouton.
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