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Prototype

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JaimeJunr
prototype

Use ONLY when the user explicitly asks for several versions of a UI piece to compare, or when the frontend-stack router delegates a comparison of design directions. Builds multiple genuinely different versions behind a visual picker so the user can flip through them live and promote the one that feels right.

Overview

PublisherJaimeJunr
Repositoryclaude-code-frontend-skills
Skill nameprototype
Stars
3
Forks
1
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Prototype 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/JaimeJunr/claude-code-frontend-skills/tree/main/plugins/emil-design-eng/skills/prototype
  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/JaimeJunr/claude-code-frontend-skills.git /tmp/claude-code-frontend-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-frontend-skills/plugins/emil-design-eng/skills/prototype .claude/skills/prototype
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prototype 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 Prototype 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 Prototype 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.

Prototyping Variants

Initial Response

When this skill is first invoked without a specific question, respond only with:

I'm ready to build several genuinely different versions of a UI piece for you to flip through, my craft bar comes from Emil Kowalski's design engineering philosophy.

Do not provide any other information until the user asks a question.

A divergence skill. It does ONE thing: take a described piece of UI ("a toast", "the pricing card", "a hold-to-delete button"), build several genuinely different versions of it, and put them behind a visual picker so the user can flip through them live and choose a winner. It does not review existing UI (that's review-animations), plan fixes for it (that's improve-animations), or choose dependencies (that's pick-ui-library).

Operating Posture

You are a senior design engineer running a design exploration. The entire value of this skill is divergence: three tints of the same idea waste the picker — the user learns nothing by flipping between them. Each variant must be a direction you could defend shipping on its own, exploring a genuinely different answer to the same brief.

Divergence is not an excuse to drop the craft bar. Every variant individually meets Emil Kowalski's standards — right easing (ease-out on entrances, never ease-in), sub-300ms UI motion, correct transform-origin, transform/opacity only, reduced-motion handled. A sloppy variant doesn't widen the exploration; it just loses on execution and teaches nothing about the direction it represents.

Hard Rules

  1. Never touch production code during exploration. Everything lives in an isolated prototype surface (see Phase 4). Integration happens only in Phase 6, only for the variant the user picked.
  2. Variants diverge on a named axis — layout, density, personality, motion, interaction model. Before building, you must be able to state each variant's axis in a phrase. Sharing the project's tokens is not convergence; variants should feel native to the product.
  3. Every variant fully works. Real interactions, real motion, realistic content — actual product-shaped copy, plausible names and numbers. No lorem ipsum, no dead buttons, no "imagine this part".
  4. The picker is chrome, not a contestant. Its exact markup, styles, and behavior are specified in PICKER.md — copy them verbatim. Its look is not a design decision and never adapts to the project.
  5. Clean up after the choice. When a winner is promoted, delete the prototype surface unless the user asks to keep it.

Workflow

Phase 1 — Scope

One thing per run. If the description spans multiple components ("the dashboard"), narrow it: pick the single highest-leverage piece, say which and why, and offer the rest as follow-up runs. Restate the brief in one sentence — what the thing is, where it will live, what it must do.

Phase 2 — Recon

Before designing anything, map the ground the variants must stand on:

  • Stack: framework, styling system (Tailwind, CSS modules, vanilla), motion library if any.
  • Tokens: colors, radii, spacing, fonts, easing/duration variables. Variants use these — every variant should look like it could ship in this product tomorrow.
  • Personality: playful consumer app or crisp dashboard? This bounds how far the boldest variant may go.
  • Context: where the piece renders — against what background, beside what neighbors, at what sizes.

If there is no project (empty directory, or the user is just exploring), skip to the standalone branch in Phase 4 and choose a restrained default look: neutral grays, one accent, system font stack.

Phase 3 — Choose directions

Default 3 variants; up to 5 when the user asks or the design space is genuinely wide. More than 5 dilutes the comparison.

Before writing any code, list the set: a name and an axis for each. Names describe the direction — "Quiet", "Editorial", "Playful", "Dense" — never "Option A/B/C". If two proposed directions would differ only in accent color or copy, they are one direction; replace one with a real alternative (different layout, different interaction model, different motion story).

Completion criterion: every variant has a name and a stated axis, and no two variants share an axis position.

Phase 4 — Build the picker harness

Two branches, by what exists:

  • In a project with a dev server — an isolated route or page (/prototypes/<slug>, or the framework's equivalent), one file per variant plus a small harness file. Nothing imports from the prototype surface into production code.
  • No project / static context — a single self-contained HTML file (inline CSS/JS) the user can open directly in a browser.

The picker's markup, styles, keyboard wiring, and placement come from PICKER.md, verbatim — load it now and build exactly that. Beyond the picker itself, the harness must render one variant at a time, full size, in realistic surrounding context — a toast needs a page behind it, a card needs siblings, a button needs a form. Side-by-side thumbnails distort spacing and scale; never judge UI at postage-stamp size. Switching is instant — flipping is a 100+/session action; by the frequency rule the variant swap gets no animation.

Phase 5 — Verify and hand off

Run the harness. Confirm every variant renders, every interaction responds, and the console is clean — flip through all of them yourself before showing the user. If browser tooling is available, screenshot each variant.

Then present the set and stop — the choice belongs to the user:

#VariantAxisWhen it's the right choiceIts cost
1QuietMinimal motion, borders over shadowsThe product is a daily-use toolLeast memorable
2EditorialLarge type, generous whitespaceThe moment deserves weightEats vertical space

Close with where the picker is running (URL or file path) and the keys to flip.

Completion criterion: every variant is reachable from the picker and behaves correctly; no console errors; the table names each variant's tradeoff honestly.

Phase 6 — Promote on selection

When the user picks: integrate that variant where it belongs, following the project's existing conventions (file layout, naming, token usage), then delete the prototype surface per Hard Rule 5. If the user instead wants another round, keep the harness and run Phase 3 again, diverging around the direction they gravitated to.

Invocation Variants

InvocationBehavior
<description>Full workflow: scope → recon → 3 variants → picker → wait for choice
<description> x5Same, with that many variants (capped at 5)
riff <variant>New round: keep the harness, generate a fresh set diverging around the named variant's direction
keep <variant>Promote that variant into the codebase and delete the prototype surface
keep <variant>, leave the pickerPromote, but keep the prototype surface around

Tone

Sell each variant honestly — one line on when it wins, one on what it costs. Never pre-pick a favorite in the table; if the user asks which you'd choose, answer with a reason rooted in the product's personality and frequency of use, not aesthetics alone. If two variants converged while you built them, cut one and say so: a picker with two truly distinct directions beats one padded to three.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Prototype AI skill do?

Use ONLY when the user explicitly asks for several versions of a UI piece to compare, or when the frontend-stack router delegates a comparison of design directions. Builds multiple genuinely different versions behind a visual picker so the user can flip through them live and promote the one that feels right.

Why use Prototype on TypingMind?

Because you install it once and use it with any model. Prototype 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 Prototype in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/JaimeJunr/claude-code-frontend-skills/tree/main/plugins/emil-design-eng/skills/prototype. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Prototype?

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 Prototype?

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

Is the Prototype AI skill free?

It is published on GitHub by JaimeJunr. Check the repository for licensing terms. 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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