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Product Screenshot Beautifier Prompt

Transform raw product screenshots into polished marketing visuals with device frames, branded backgrounds, annotations, and feature callouts.

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Your Prompt
prompt.txt
Create a product screenshot beautification system for TaskPilot marketing materials. The product is a project management web application with a clean, minimal with a light theme and purple accents interface. Design the following treatments: 1) Hero screenshot treatment — describe a MacBook Pro 16-inch mockup with the screenshot at a slight 3D perspective tilted 5 degrees angle, placed on a abstract mesh gradient with soft geometric shapes background with the brand gradient (from #667EEA to #764BA2) as an accent. Add a subtle shadow with 0 25px 50px rgba(0,0,0,0.15) with 10px blur and a reflection effect. 2) Feature callout version — take the screenshot and add 4 numbered annotation bubbles pointing to key UI elements, each with a short label and connecting line. Use pill-shaped badges with connecting dotted lines style for the annotations. Describe the exact placement, color coding, and typography for each callout. 3) Before/After comparison — create a split-screen layout showing the old dashboard vs. the redesigned dashboard, with a draggable divider indicator in the center, "Before" and "After" labels, and matching device frames on both sides. 4) Multi-device showcase — arrange the screenshot across MacBook, iPad, and iPhone in an isometric or perspective layout, showing responsive design. Describe the spatial arrangement, size ratios, and how they overlap. 5) App Store/marketplace version — format the screenshot to meet Apple App Store (6.5-inch display format) requirements with device frame, promotional text overlay (headline + subtitle), and the exact dimensions and safe zones. 6) Social media version — crop and reframe the screenshot for LinkedIn feed post (1200x627px) posts, adding context text, the brand logo watermark, and a branded border. 7) Create a Figma/design tool template specification so the marketing team can apply these treatments to future screenshots using Figma with auto-layout components.

What this prompt does

This prompt creates a product-screenshot beautification system that turns raw app screenshots into polished marketing visuals. You provide [product_name], the [product_type], and the [ui_style], and ChatGPT describes a set of treatments: a hero mockup with a device frame, a feature-callout version, a before/after comparison, a multi-device showcase, marketplace and social formats, and a reusable template spec.

The variables define the visual treatment precisely. [device_frame] and [hero_angle] set the mockup, [background_type] and [brand_gradient] shape the backdrop, and [shadow_specs] give the exact shadow. [callout_count] and [callout_style] control the annotation layer, [comparison_context] defines the before/after subject, and [device_types] lists the devices for the multi-device shot. [marketplace], [social_platform], and [template_tool] cover the export formats and the template specification. Because every treatment comes with placement, color, and typography direction, the output briefs a designer or image tool on exactly what to build.

When to use it

  • You have raw app screenshots and want them turned into polished marketing visuals.
  • You are launching a feature and a bare screenshot undersells it without a device frame and callouts.
  • You need a before/after comparison to show a redesign or improvement clearly.
  • You want a multi-device showcase demonstrating responsive design in one image.
  • You need marketplace-compliant and social-sized versions of the same screenshot.
  • You want a reusable template so your team can beautify future screenshots consistently.

Example output

The output is a set of treatment specifications. It describes a hero shot with a [device_frame] at [hero_angle] on a [background_type] background with [brand_gradient] and [shadow_specs], a callout version with [callout_count] numbered annotations in [callout_style], a before/after split showing [comparison_context], a multi-device layout across [device_types], a [marketplace]-formatted version with promotional text, a [social_platform] crop with watermark, and a [template_tool] template spec so the treatments are repeatable. You then render each in a design tool or image generator.

Pro tips

  • Pick a [device_frame] that matches where the product actually lives — a MacBook frame for a web app, a phone frame for mobile.
  • Keep [callout_count] to the handful of features that matter; too many annotations clutter the shot and bury the message.
  • Make [comparison_context] a genuine before/after; the treatment only lands when the improvement is real and visible.
  • Set [brand_gradient] and [shadow_specs] to your real brand values so the visuals stay on-brand across releases.
  • The output describes treatments, not finished images, so pair it with a screenshot and a design tool to produce them.
  • Build the [template_tool] spec once and reuse it, so every future release gets consistent marketing visuals without restarting.
  • Match the [device_types] in the multi-device showcase to where your product genuinely runs, since showing a mobile frame for a desktop-only tool misleads viewers.
  • Tune [social_platform] to where you actually post, because the crop and aspect ratio differ enough that a LinkedIn-sized visual looks wrong on other feeds.

Frequently Asked Questions

Does this prompt edit my actual screenshots?
No, it describes the beautification treatments in detail but does not process images. You apply the device frames, callouts, and backgrounds yourself in a design tool, or feed the spec plus your screenshot to an image-generation model.
Can it make App Store-ready screenshots?
Yes, one treatment formats the screenshot to meet `[marketplace]` requirements with a device frame, promotional text, and the right dimensions and safe zones. You should still verify the marketplace's current specs, since store requirements change over time.
Will the callouts point to the right UI elements?
The prompt specifies the number, style, and placement logic for `[callout_count]` annotations, but it cannot see your actual screenshot. You position the callouts on the real UI elements yourself, using the placement and styling direction it provides.
Is the template reusable across future releases?
Yes, the final step produces a template specification for a tool like Figma so your team can apply the same treatments to future screenshots. Building it once gives every release consistent marketing visuals without redesigning from scratch each time.
Engr Mejba Ahmed

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Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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