hschickdevs

Genui — Design skill for Claude Code

Design community

Agent harness whose only output is generated UI: Opus plans, a warm Haiku pool streams interactive panels.

How to install Genui

This entry records only its repository, not the path inside it, so there is no exact command to give. Open hschickdevs/genui and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Genui does

Agent harness whose only output is generated UI: Opus plans, a warm Haiku pool streams interactive panels. Built on the Claude Agent SDK.

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README

![genui](docs/logo-lockup.svg)

A properly prompted modern LLM (Gemini 3) can robustly generate a full custom interactive web page for almost any prompt. Humans prefer it over markdown 82.8% of the time.

— summarized from Leviathan et al., [*Generative UI: LLMs are Effective UI Generators*](https://arxiv.org/pdf/2604.09577), Google Research ([blog](https://research.google/blog/generative-ui-a-rich-custom-visual-interactive-user-experience-for-any-prompt/), [examples](https://generativeui.github.io))

**genui is Claude Code without the chat window: a coding agent whose only output is interfaces it generates on the fly.** Ask about your code and, instead of a wall of markdown, you get a custom panel built for that answer: an architecture diagram, a diff to approve, a table of test results, buttons for next steps. You can click and comment on any part of it. It runs locally in your browser on your existing Claude Code login; run `genui` in a project to start.

It stays fast through orchestration: a strong model (Opus or Fable) does the thinking and writes a short brief, and pre-warmed fast models (Haiku) stream each brief into a panel. Panels start appearing in **~0.5–3 seconds instead of 1–2 minutes**. [Why this works →](#why-genui)

![Demo, real time](docs/demo.gif)

*Real-time capture, not sped up. Full video: [docs/demo.webm](docs/demo.webm).*

Contents

Why genui

The paper shows people strongly prefer generated interfaces, but measured that *"when ignoring generation speed."* Its implementation has one model write each full page. genui keeps the paper's prompting principles (Appendix A.5) and post-processing ideas (A.6), and changes the architecture to remove both costs:

Paper's limitation genui's answer
1–2 minutes per page (streaming only halves the perceived wait) A strong planner writ