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Mockuplm

OrganizationPopular
nimbalyst
mockuplm

Create visual UX mockups using HTML/CSS files (.mockup.html). Use when the user wants to design UI, wireframes, visual layouts, or plan features visually.

Overview

Publishernimbalyst
Repositorynimbalyst
Skill namemockuplm
Stars
1.9K
Forks
300
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 nimbalyst on GitHub. Read the source before you install it.

Installation

Install the Mockuplm 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/nimbalyst/nimbalyst/tree/main/packages/extensions/mockuplm/claude-plugin/skills/mockuplm
  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/nimbalyst/nimbalyst.git /tmp/nimbalyst
mkdir -p .claude/skills
cp -r /tmp/nimbalyst/packages/extensions/mockuplm/claude-plugin/skills/mockuplm .claude/skills/mockuplm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mockuplm 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 Mockuplm 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 Mockuplm 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.

MockupLM - Visual Planning

MockupLM is Nimbalyst's visual mockup system for UI/UX design and planning. Create .mockup.html files with HTML and inline CSS to share and iterate on designs with users.

When to Use MockupLM

  • Planning new UI features or screens
  • Designing layouts and visual hierarchy
  • Creating wireframes or prototypes
  • Visualizing proposed changes to existing screens
  • Any situation where visual communication helps

Do NOT use for implementation - MockupLM is for planning only. If you're implementing actual code, don't create mockup files.

File Format

  • Extension: .mockup.html
  • Location: nimbalyst-local/mockups/ for new designs, nimbalyst-local/existing-screens/ for replicas of existing UI
  • Structure: Standalone HTML with inline CSS, no external dependencies
html
<!DOCTYPE html>
<html>
<head>
  <style>
    /* Inline CSS here */
  </style>
</head>
<body>
  <!-- Mockup content -->
</body>
</html>

Workflow

  1. Create mockup file in nimbalyst-local/mockups/[descriptive-name].mockup.html
  2. Build the mockup with HTML and inline CSS
  3. Verify visually using the Task tool to spawn a sub-agent that will:
    • Capture screenshot with mcp__nimbalyst__capture_editor_screenshot
    • Analyze for layout/visual issues
    • Fix with Edit tool if needed
    • Re-capture and iterate until correct

User Annotations

Users can draw directly on mockups in the editor (circles, arrows, highlights). These annotations are NOT in the HTML source.

To see user annotations: Use mcp__nimbalyst__capture_editor_screenshot to capture a screenshot that includes the annotations.

When the user draws on a mockup:

  1. Capture a screenshot to see what they marked
  2. Interpret their visual feedback
  3. Update the mockup accordingly

Design Guidelines

  • Realistic appearance: Mockups should look like finished UI, not sketches
  • Clean HTML/CSS: Use semantic HTML and minimal, well-organized CSS
  • Stable selectors: When regenerating a mockup, preserve existing id and class values on elements that still represent the same UI; rename or remove them only when that element genuinely changes
  • Modern patterns: Use flexbox, grid, CSS variables
  • Placeholder content: Use realistic sample data (lorem ipsum, example names, etc.)
  • Responsive design: Consider mobile breakpoints when appropriate

For Existing Screens

When modifying existing UI:

  1. Check nimbalyst-local/existing-screens/ for cached replicas
  2. If no replica exists, create a pixel-perfect HTML/CSS replica first
  3. Copy to nimbalyst-local/mockups/ and apply modifications there
  4. Never modify the original in existing-screens directly

File Naming

Use kebab-case with .mockup.html extension:

  • settings-page.mockup.html
  • checkout-flow.mockup.html
  • user-profile-card.mockup.html

Frequently asked questions

What does the Mockuplm AI skill do?

Create visual UX mockups using HTML/CSS files (.mockup.html). Use when the user wants to design UI, wireframes, visual layouts, or plan features visually.

Why use Mockuplm on TypingMind?

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

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

Which AI models can use Mockuplm?

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 Mockuplm?

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

Is the Mockuplm AI skill free?

Yes. It is published on GitHub by nimbalyst 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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