Dembrandt logo

Dembrandt

Organization
dembrandt
dembrandt

Orchestrator that routes a UI/UX task through brand, tokens, layout, components, polish and accessibility. Use for multi-concern work such as a design review, UI build or interface audit.

Overview

Publisherdembrandt
Repositorydembrandt-skills
Skill namedembrandt
Stars
169
Forks
21
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dembrandt on GitHub. Read the source before you install it.

Installation

Install the Dembrandt AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dembrandt/dembrandt-skills/tree/main/skills/dembrandt
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dembrandt/dembrandt-skills.git /tmp/dembrandt-skills
mkdir -p .claude/skills
cp -r /tmp/dembrandt-skills/skills/dembrandt .claude/skills/dembrandt
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dembrandt in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dembrandt on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dembrandt is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

dembrandt — UX Pipeline Orchestrator

Concept by @VictorGjn.

Routes multi-concern UI/UX tasks through six ordered stages. Each stage loads sub-skills on demand — only what the task actually needs.

When to use this skill vs a sub-skill directly:

  • Multi-concern task ("design review", "audit interface", "build UI") → use this orchestrator
  • Single-concern task ("check my colour palette", "review button states") → go directly to the sub-skill
  • Brand-to-token-to-spec pipeline with a URL or DESIGN.md → use generate-ui-from-brand instead
  • Reproducing an existing page rather than designing one → use clone-website instead
  • Reading the tokens off a live site and nothing more → use extract-design instead

Pipeline

Stage 1 — Brand Foundation

Establish the visual language before making any token decisions.

Sub-skills (load as needed):

  • brand-visual-language — shape language, icon style, typography tone
  • algorithmic-color-palette — derive states and brand-tinted greys from brand colours
  • color-mode-and-theme — light vs dark vs combined, when to offer a theme selector

Gate: Brand tone and colour system agreed before proceeding.


Stage 2 — Design Tokens & Scales

Pin the numeric system so all components share a common foundation.

Sub-skills (load as needed):

  • modular-scale-typography — ratio-based type scales, minimum sizes, context-aware usage
  • elevation-and-depth — shadow scale, border-radius, card and modal patterns
  • surface-separation — one means per surface: border, elevation or fill; opacity is for state
  • button-states — six states: rest, hover, active, focus, disabled, loading
  • component-family-consistency — buttons, inputs, pills: shared radius, colour, height
  • sizing-units — px vs rem vs relative: which values move when the user enlarges text
  • status-colors-and-errors — minimal semantic colours, error recovery, prevention

Gate: Tokens defined and consistent across component family.


Stage 3 — Layout & Structure

Apply layout decisions to the specific product context.

Sub-skills (load as needed):

  • layout-paradigms-and-consistency — choose the layout paradigm that fits the content; reuse the same page skeleton across screens (macro-scale consistency)
  • gestalt-ui-organisation — group related controls: proximity, similarity, common region
  • visual-emphasis-and-hierarchy — one CTA per view, colour and size as emphasis
  • information-architecture — naming, mental models, data UI, confirm dialogs
  • ui-context-and-scope — hierarchy, breadcrumbs, colour regions, scope communication
  • marketing-vs-product-system — site and product differ in density, share one token layer
  • responsive-paradigms — mobile/tablet/desktop: nav, sections, sticky behaviour
  • ui-density — match density to platform and user type
  • sticky-and-fixed-elements — headers, bottom toolbars, z-index tokens
  • scroll-areas — avoid inner scroll, one axis only, user-controlled

Gate: Layout is coherent across breakpoints and user contexts.


Stage 4 — Components & Interaction

Review component patterns and interactive states.

Sub-skills (load as needed):

  • real-world-metaphors — cards, carousels, drawers: when to use and how
  • tab-navigation — tab types, overflow, keyboard nav, ARIA, state persistence
  • modal-and-overlay-patterns — tooltip/popover/drawer/modal hierarchy, focus management, destructive confirm
  • form-design — helper text, placeholder, validation, submit state
  • data-display-and-selection — grid/list/table, large hit areas, mass actions
  • repeated-component-alignment — repeated components as slot models: equal size, pinned anchors, clamp + recover overflowing text
  • operational-expert-tool-ui — dense, workflow-driven UIs for trained daily B2B users
  • coordinated-data-views — keep a table and a visual view (map, diagram, chart) synchronized
  • domain-expert-configuration — expose solver/algorithm settings in domain language
  • authentic-product-representation — real content and real output over staged mockups and marketing chrome
  • app-shell — top bar, app launcher, tenant and environment cue, status bar: one shell across an estate
  • global-toolbar-controls — currency, language, region and unit selectors
  • notifications-and-recovery — toasts, banners, retry, undo — always a path forward

Gate: All interactive states handled; no dead ends.


Stage 5 — UX Polish

Apply UX principles and motion to sharpen perceived quality.

Sub-skills (load as needed):

  • nielsen-usability-heuristics — 10 usability principles with review checklists
  • user-flows-and-guided-paths — wizards, purchase flows, onboarding sequences
  • micro-interactions — animated icons, toggles, reveals, celebrations
  • loading-states-and-perceived-performance — spinners, skeleton screens, staggered entry
  • motion-and-storytelling — Disney principles and cinematic language in UI

Gate: Flow is legible end-to-end; perceived performance is acceptable.


Stage 6 — Accessibility & Technical Gate

Hard ship gate. Do not skip or defer.

Sub-skills (load as needed):

  • wcag-accessibility — WCAG 2.2 AA / EN 301 549: contrast, keyboard, ARIA
  • semantic-html-and-seo — HTML5, alt texts, Open Graph, progressive enhancement
  • performance-and-web-vitals — Lighthouse audit, LCP, CLS, INP, images, fonts, JS loading

Gate: Passes WCAG 2.2 AA. Required by EU Accessibility Act (EAA) for products launched after June 2025.


Output

Produce one structured review, not a stream of loose comments. Group findings by severity, most blocking first:

  1. Blockers — fails a hard gate: WCAG 2.2 AA, a broken flow, a dead end. Must fix before ship.
  2. Major — breaks consistency, hierarchy, or a core UX principle. Fix this iteration.
  3. Minor — polish, micro-interactions, perceived-performance refinements. Backlog.

For each finding give the stage it came from, the specific element, what is wrong, and the concrete fix.

Run only the stages the task needs. An existing product with settled brand and tokens starts at Stage 3; a pure accessibility pass runs Stage 6 alone. State which stages you ran and which you skipped, and why.


Relationship to generate-ui-from-brand

generate-ui-from-brand is a token-extraction pipeline: URL or DESIGN.md → tokens → UI spec. It overlaps stages 1–2 of this orchestrator. Use it when you have a brand source and need a concrete spec. Use this orchestrator when you are reviewing or building across the full stack of UX concerns without a specific brand-extraction starting point.

Frequently asked questions

What does the Dembrandt AI skill do?

Orchestrator that routes a UI/UX task through brand, tokens, layout, components, polish and accessibility. Use for multi-concern work such as a design review, UI build or interface audit.

Why use Dembrandt on TypingMind?

Because you install it once and use it with any model. Dembrandt is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dembrandt in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dembrandt/dembrandt-skills/tree/main/skills/dembrandt. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dembrandt?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dembrandt?

As many as you like. As long as a model supports skills, you can use Dembrandt with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dembrandt AI skill free?

Yes. It is published on GitHub by dembrandt under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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