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Shape

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educlopez
shape

Wireframe-first pass — outputs an ASCII layout + state list + content inventory + question list before any code. Use when starting a new screen from scratch or when the user's brief is still ambiguous. Invoke when the user asks for shape on their UI, or mentions 'shape' alongside design / UI / frontend work.

Overview

Publishereduclopez
Repositoryui-craft
Skill nameshape
Stars
344
Forks
17
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 educlopez on GitHub. Read the source before you install it.

Installation

Install the Shape 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.
  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/educlopez/ui-craft.git /tmp/ui-craft
mkdir -p .claude/skills
cp -r /tmp/ui-craft/cli/assets/codex/skills/shape .claude/skills/shape
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Shape 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 Shape 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 Shape 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.

Context: this sub-skill is one lens of the broader ui-craft skill. If the ui-craft skill is also installed, read its SKILL.md first for Discovery + Anti-Slop + Craft Test, then apply the specific lens below.

Shape the UI for $ARGUMENTS before writing code. Load the ui-craft skill.

This command produces a shape artifact, not JSX. The point is to force low-fi thinking — content inventory, layout regions, state coverage, open questions — before any component is written. Skipping this step is how generic AI UIs get built: straight to hi-fi, no discovery, every screen looks the same.

Step 1 — Clarify (3-5 questions). Ask the user before shaping. Don't guess. Minimum questions:

  • What's the primary user action on this screen? (One verb, one object.)
  • What data is visible by default vs hidden behind a click or tab?
  • What does success look like — a state, a redirect, a toast?
  • Who's the primary user — first-timer, power user, mobile-first?

Step 2 — Content inventory. Bullet list of every piece of content that will appear. Annotate each by priority:

  • P0 — must be visible on first paint. Cut it and the screen fails.
  • P1 — one click away (tab, accordion, drawer).
  • P2 — settings-level; rarely accessed.

Example:

- P0  Headline (one line, the value prop)
- P0  Primary CTA
- P0  Hero chart / metric
- P1  Secondary nav tabs
- P1  Recent activity list
- P2  Export / integrations menu

Step 3 — ASCII layout. Low-fi sketch showing regions. No specific copy, no colors, no font sizes. One desktop variant + one mobile variant. Use box characters:

Desktop
┌──────────────────────────────────────────────┐
│ [logo]                 [nav]         [user]  │
├──────────────────────────────────────────────┤
│  ┌────────────────┐   ┌───────────────────┐  │
│  │ Headline + sub │   │                   │  │
│  │                │   │   Hero visual     │  │
│  │ [Primary CTA]  │   │                   │  │
│  └────────────────┘   └───────────────────┘  │
│                                              │
│  ── Social proof row ──                      │
│                                              │
│  ┌─── Feature 1 ───┐   ┌─── Feature 2 ───┐   │
│  └─────────────────┘   └─────────────────┘   │
└──────────────────────────────────────────────┘

Mobile
┌──────────────────┐
│ [logo]     [☰]   │
├──────────────────┤
│  Headline + sub  │
│                  │
│  [Primary CTA]   │
│                  │
│  ┌── Hero ──┐    │
│  └──────────┘    │
│                  │
│  Social proof    │
│                  │
│  Feature 1       │
│  Feature 2       │
└──────────────────┘

Asymmetry is fine and often better — don't force center-everything.

Step 4 — State list. Enumerate the states this screen must handle. Point at references/state-design.md for the contracts.

  • idle — default state, data present.
  • loading — skeletons that mirror final layout, 200ms delay before showing.
  • empty — first-run or no data; doubles as onboarding.
  • error — specific cause + recovery action + support ID.
  • partial — some data loaded, some failed (e.g., one widget erred).
  • conflict — user-edit collision (rare but load-bearing on collaborative surfaces).
  • offline — queue writes, reconcile on reconnect.
  • success — confirmation state after the primary action completes.

Mark each as required / optional (why) / N/A.

Step 5 — Open questions. Do NOT start coding until these are answered. Default set:

  • Accent color — brand-defined, or to be chosen? (See Discovery in SKILL.md.)
  • Typography — existing tokens, or new system? (Reference typography.md.)
  • Responsive breakpoints — what's the minimum supported width?
  • Stack — CSS only, or Motion / GSAP / Three.js? (Only load stack.md if the user opts in.)
  • Data source — real API ready, or mock for shape?
  • Keyboard / a11y requirements — anything beyond the baseline from accessibility.md?

Knob awareness.

  • At CRAFT_LEVEL ≥ 7, add two more sections:
    • Motion shape — which elements enter, in what order, with what stagger. Pick from the duration scale in references/motion.md.
    • Typography hierarchy plan — display / headline / body / label sizes and weights, before code.
  • At CRAFT_LEVEL ≤ 4, strip Step 4 to idle / loading / error only. Skip the motion shape.

Step 6 — Offer to persist to .ui-craft/spec.md (opt-in).

After printing all five steps, offer to write the output as a spec section:

"Write this shape to .ui-craft/spec.md as ## Surface: <name>? (Persists the composition choice, layout, and acceptance bar for the build phase.)"

  • User confirms → format the output as a ## Surface: <name> section following the template in ../skills/ui-craft/references/spec.md, then write or append to .ui-craft/spec.md. Confirm in one line: "Written to .ui-craft/spec.md## Surface: <name>."
  • User declines → do not write any file. The printed output stands. Note: "spec.md not written — the pipeline continues without a persisted acceptance bar."

Print-only is the default when /shape is run standalone. Step 6 is the offer; it does not execute unless the user explicitly confirms.

Output contract.

  • Produce a single Markdown block with all five steps, in order. Step 6 is the optional offer that follows.
  • Do NOT write JSX, CSS, or component code in this command.
  • End the output with: "Ready to build? Review the shape, confirm the open questions, then run /ui-craft:audit (or use Build mode) once the code exists."

Next step: /craft — build the surface you just wireframed (rung 1).

Frequently asked questions

What does the Shape AI skill do?

Wireframe-first pass — outputs an ASCII layout + state list + content inventory + question list before any code. Use when starting a new screen from scratch or when the user's brief is still ambiguous. Invoke when the user asks for shape on their UI, or mentions 'shape' alongside design / UI / frontend work.

Why use Shape on TypingMind?

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

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

Which AI models can use Shape?

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 Shape?

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

Is the Shape AI skill free?

Yes. It is published on GitHub by educlopez 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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