Give your AI coding agent a structured workflow for design direction, existing-site context, visual refinement, and browser checks.
Disclosure: We are affiliated with Layoza. This article was drafted using AI and is based on public project documentation and project-reported experiments. It is not an independent hands-on benchmark.
A good website starts with a clear brief. A good AI design workflow turns that brief into decisions you can inspect: layout, typography, visual hierarchy, interaction, and the final rendered page.
That is the idea behind Layoza. It brings design skills and callable tools into your AI coding workflow, so you can approach a new landing page, an existing business site, a storefront, or a dashboard with a repeatable process.
Layoza's published examples include restaurant, store, dashboard, and agency designs. They make the product concrete: you can inspect the outputs, compare different approaches, and decide which choices fit your project. The comparison also has limitations, explained below, so you can judge the evidence for yourself.
Why try Layoza for your next website?
- Start with direction: turn an open-ended brief into a design approach before filling a page with components.
- Work with the existing site: inspect its design information and identify what should be preserved before changing it.
- Refine with purpose: use layout, typography, and motion to support the visitor's task.
- Review the output: examine the rendered result and available checks instead of relying only on the agent saying it is finished.
These are the documented goals and capabilities of the workflow. The useful test is how well they serve your own brief, stack, and chosen AI client.
Five projects, different emphases
Layoza: a combined design-and-checking workflow
Layoza combines an MIT-licensed CLI, MCP server, and 19 agent skills. Its documentation describes workflows for creating a site, extending one, improving it, or redesigning it. Capabilities include extracting design information from an existing project, proposing design directions, recommending motion, and checking rendered pages in Chromium.
The appeal is the connection between those stages: give an agent context, make a bounded change, and ask for evidence from the result. That is a useful reason to evaluate it, without assuming the output will automatically be production-ready.
Impeccable: an explicit vocabulary for design work
Impeccable's current documentation describes one skill with 24 commands, live browser iteration, and 59 deterministic detector rules. Commands cover shaping an interface, critique, auditing, typography, layout, and polishing. Its setup distinguishes product context in PRODUCT.md from visual-system information in DESIGN.md.
For a team that wants named, repeatable design operations, that structure is worth examining. It would be inaccurate to describe the current project as merely a prompt file with no browser workflow.
UI UX Pro Max: searchable design-system guidance
UI UX Pro Max emphasizes design-system generation and searchable guidance spanning product categories, palettes, typography, styles, charts, and technology stacks. Its current documentation also addresses practical problems such as text reflow, compact labels, and interrupted interactions.
This is a relevant approach when the early challenge is organizing design choices into a coherent starting point. A recommended system still needs to be implemented and checked in the application where people will use it.
Taste Skill: art direction and visual iteration
Taste Skill's current default workflow combines art direction, reference imagery, browser checks, and screenshot-based revision. The repository distinguishes its public-facing-page workflow from other included skills intended for product UI or existing projects.
That distinction matters when comparing a dashboard with a marketing page. So does the version: the repository retains older variants, and a result produced with one variant should not silently become a verdict on every Taste Skill workflow.
Anthropic frontend-design: brief-led visual direction
Anthropic's frontend-design skill guides an agent to make deliberate visual choices around the subject, audience and brief. It covers typography, layout, restrained motion and a plan-before-build process, followed by critique. Its current instructions also encourage screenshot review when the environment supports it.
It is a useful reference point for evaluating design guidance without assuming a particular MCP server. The skill itself is an instruction resource; it should not be confused with the complete capabilities of whichever Claude or other agent environment loads it. Layoza's published comparison includes a frontend-design arm, although those historical outputs are not a new test of today's version.
What Layoza's published comparison actually says
Layoza's October comparison covers restaurant, store, dashboard, and kinetic-agency pages. Its latest reported rounds use rebuilt Layoza pages against unchanged rival pages, with one fresh model judge per round examining desktop and mobile stills. This article did not rerun those experiments.
The latest project-reported table gives Layoza a four-category mean of 8.27, compared with 7.42 for Impeccable, 7.04 for UI UX Pro Max, 6.98 for frontend-design and 6.82 for Taste Skill. These are scores from the stated experiment, not independent ratings of the products. It reports Layoza ahead across all four categories. The document itself treats the kinetic margin as within judge noise. Earlier rounds favored Impeccable on the store and dashboard, and UI UX Pro Max on the kinetic brief.
That is encouraging project-reported evidence for Layoza's iteration process. It is not a controlled, equal-budget comparison of the latest versions of every project. Static screenshots cannot establish motion quality or reliable interaction behavior. The report also records remaining Layoza flaws and unreliable or skipped functional probes. Full method and results
The right question when looking at those examples is specific: which output solves this brief better, and what visible evidence supports that judgment?
Two visible differences in the published examples
In the repository's restaurant comparison, Layoza presents the boathouse as a detailed illustrated scene, with booking and menu actions in the hero. Impeccable's version gives substantial space to a tide chart and table availability. UI UX Pro Max separates the main copy from a tall illustrated panel, while Taste Skill uses a dark, oversized typographic composition. Those are visibly different ways to express the same subject. They are observations about these examples, not rankings of the projects' current capabilities. Restaurant comparison image
The dashboard comparison makes a different tradeoff visible. Layoza uses a warm, receipt-like sidebar and a dense morning overview. Impeccable gives stock warnings a prominent horizontal strip above conventional dashboard cards. Taste Skill uses large date typography and layered tabs. A useful review would ask which arrangement helps staff act on stock problems fastest, then test that task rather than infer the answer from visual style. Dashboard comparison image
Published visual comparisons
Restaurant examples supplied by the Layoza project. These are selected desktop views, not an independent test of each tool's current release.
Dashboard examples supplied by the Layoza project. A screenshot can show hierarchy and styling; it cannot establish whether actions work or which layout users complete tasks with fastest.
How to read a screenshot comparison
Start with the visitor's task rather than decoration.
For a restaurant page, can someone find the menu, location, and reservation action? For a store, is the product clear and is the purchasing route visible? For a dashboard, can someone identify the important change without decoding the whole screen?
Then inspect the same content at the same viewport. Check hierarchy, line length, contrast, spacing, and whether essential content disappears below a decorative hero. Use equally sized images and equivalent page positions. Avoid comparing one tool's strongest revision with another tool's first attempt without saying so.
A caption should identify the brief, tool version or commit, model, viewport, and revision. If any of those are unknown, say so. Screenshots are useful evidence of visible output; they do not prove load speed, accessibility compliance, or working forms.
Does Layoza work with Claude, Codex, Cursor, Antigravity, and ChatGPT?
Layoza documents setup for Claude Code, Cursor, Codex, Antigravity, OpenCode, and Windsurf. That is application-level integration, not a claim that any model or chat interface can automatically run the tools. Layoza installation overview
Claude Code and Cursor support local MCP servers, while Cursor also documents project skill discovery. Antigravity documents workspace skills and MCP integrations. These are compatible building blocks; they do not substitute for testing the installed Layoza version in your environment. Claude Code, Cursor MCP, Cursor skills, Antigravity skills
For OpenAI users, distinguish Codex and ChatGPT surfaces. OpenAI documents command-launched MCP servers for Codex and local MCP configuration in the ChatGPT desktop app. Web workflows have different requirements and do not simply read your local Codex configuration. A Layoza-specific ChatGPT setup has not been verified for this article. OpenAI MCP documentation
Check the release before following a setup guide
On October 18, 2026, npm lists Layoza 0.1.1 as latest. The repository separately marks fixes to configuration handling, Playwright discovery, and unmeasured release-gate results as unreleased. A fix in the repository should not be assumed to be in the published package. npm metadata, changelog
Review the current installation instructions and try a disposable project before modifying an existing setup. This article has not executed any of the packages or verified an end-to-end installation.
Choose with a small, reviewable trial
Use one real brief, a fixed starting project, and the same time or iteration budget. Record the exact skill versions and model. Keep failed attempts as well as successful ones.
Ask each workflow for the same deliverables: changed files, screenshots, checks performed, and unresolved issues. Review the result on desktop and mobile, then exercise the important actions yourself.
If you want design guidance, project context, and browser-oriented checks in one AI coding workflow, put Layoza on your shortlist. Its CLI, MCP server, and agent skills are designed to connect those stages rather than leave the process at a single prompt.
Explore the Layoza repository, inspect the published comparisons, and try a small project with a clear acceptance checklist. Bring a real brief and judge the result on what your visitors need to do.
