imagegen-frontend-web

Generate horizontal front-end design references for landing page sections.

3|Updated Jul 30, 2026
One-click install
npx skills add https://github.com/Hayatelin/taste-skill-zh-CN --skill imagegen-frontend-web-hayatelin
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: imagegen-frontend-web
Source: https://github.com/Hayatelin/taste-skill-zh-CN/tree/main/skills/imagegen-frontend-web
Command: npx skills add https://github.com/Hayatelin/taste-skill-zh-CN --skill imagegen-frontend-web-hayatelin

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you avoid generic, AI-looking website layouts by generating high-end front-end design references that feel art-directed, conversion-aware, and easy to implement.

Core Features & Use Cases

  • One section, one image: Produces a separate horizontal image for each website section instead of collapsing the whole page into one mockup.
  • Strong visual direction: Encourages varied hero compositions, background treatments, typography scales, and CTA styles so pages feel intentional rather than template-based.
  • Front-end ready comps: Optimized for landing pages, marketing sites, product sites, portfolios, and other web experiences where developers or coding models need a clear visual blueprint.
  • Use Case: A designer asks for an 8-section SaaS marketing site, and this Skill generates eight distinct section references with consistent branding, clear hierarchy, and implementation-friendly structure.

Quick Start

Use the imagegen-frontend-web skill to generate a premium 6-section landing page concept with distinct horizontal images for each section.

Frequently Asked Questions about imagegen-frontend-web

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

FAQPage Schema
How do I generate high-fidelity website mockups for a landing page?

To generate high-fidelity website mockups, this Skill produces art-directed, front-end design references for landing pages, outputting a separate horizontal image for each section. It applies strong visual direction to typography, spacing, and conversion hierarchy so developers can accurately recreate the design.

Can I get individual section images for a SaaS marketing site instead of one long page?

Yes, you can get individual section images for a SaaS marketing site. This Skill generates one distinct horizontal image per section, such as hero sections, trust bars, feature grids, and pricing layouts, ensuring consistent brand continuity across the entire page mockup.

What is the best way to create front-end design references that are easy to implement?

The best way to create implementation-friendly front-end design references is using a conversion-aware mockup generator. This Skill provides clear visual blueprints with varied composition, typography scales, and CTA styles, preventing generic AI-looking layouts and helping coding models build accurately.

Does this approach work for designing multiple landing page sections with consistent branding?

Yes, this approach works for designing multiple landing page sections with consistent branding. By generating a separate horizontal mockup for each section, it maintains strong visual direction and brand continuity across hero areas, testimonials, and CTA layouts for a cohesive marketing site.

Why do AI-generated landing page designs often look generic and template-based?

AI-generated landing page designs often look generic because they lack intentional art direction and conversion hierarchy. This Skill solves that by applying varied hero compositions, background treatments, and typography scales to produce premium, implementation-ready front-end design references.

What sections are supported when generating marketing website mockups?

When generating marketing website mockups, supported sections include hero sections, trust bars, feature grids, testimonials, pricing, and CTA layouts. Each section receives a distinct horizontal image with clear visual hierarchy optimized for front-end implementation.