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Explorer Interface Brief

CommunityPopular
mohitagw15856
explorer-interface-brief

Use when asked to design the interface for an interactive 3D explorer, plan a UI for exploring a 3D model of a topic, or write an image-model prompt for a 3D learning app mock-up. Produces, from a topic, the UI design brief (audience, layout, panels, interactions, label style, colour palette, accessibility) and an image-model prompt for the interface mock. First step of explorer-pipeline.

Overview

Publishermohitagw15856
Repositorypm-claude-skills
Skill nameexplorer-interface-brief
Stars
1.4K
Forks
257
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 mohitagw15856 on GitHub. Read the source before you install it.

Installation

Install the Explorer Interface Brief 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/mohitagw15856/pm-claude-skills/tree/main/plugins/pm-3d-explorer/skills/explorer-interface-brief
  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/mohitagw15856/pm-claude-skills.git /tmp/pm-claude-skills
mkdir -p .claude/skills
cp -r /tmp/pm-claude-skills/plugins/pm-3d-explorer/skills/explorer-interface-brief .claude/skills/explorer-interface-brief
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Explorer Interface Brief 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 Explorer Interface Brief 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 Explorer Interface Brief 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.

Explorer Interface Brief

A 3D explorer (a heart, a jet engine, a cell, a volcano) succeeds or fails on its interface: where the model sits, how labels read against it, how a learner moves between free exploration and testing themselves. This skill turns a topic into a design brief a builder can follow and an image-model prompt that produces a convincing mock of the screen before any 3D work starts.

Required Inputs

Ask for these if not provided:

  • Topic and the specific object or system to explore
  • Audience: age or level (for example 14-year-old students, first-year medical students, museum visitors)
  • Learning goal: what the learner should be able to name, explain or do afterwards
  • Devices: classroom laptops, phones, a museum touch screen
  • Brand or colour constraints, if any

Output Structure

1. Design brief

  • Purpose: one sentence: who explores what, to learn what
  • Audience notes: reading level, prior knowledge, device and setting
  • Learning outcomes: three to five, each starting with a verb (name, locate, explain)
  • Layout: the model stage, a side panel (or bottom sheet on phones) with the selected part's label, description and source, a parts list, and a toolbar (exploded view, quiz mode, reset). Give proportions for desktop and phone.
  • Interactions: rotate, zoom, select (click, tap and keyboard via the parts list), exploded view, quiz mode, reset. State the response to each.
  • Label style: font, size (at least 16 px body), casing, how labels attach to parts (side panel rather than floating text over geometry), and what a "source" line looks like
  • Colour palette: background, panel, ink, accent and highlight as hex values, each pair checked for at least 4.5:1 contrast for text; a dark-mode variant
  • Accessibility: keyboard path to every part, visible focus, reduced motion respected, no information carried by colour alone
  • Content rules: every label carries a named source; the model is described as illustrative

2. Image-model prompt for the interface mock

A single prompt in this structure, ready for an image model:

UI mock-up, [device] screen, [width]x[height] aspect, of an interactive 3D explorer for [topic].
Left: [model description] on a [background colour] stage, three-quarter view, soft studio light.
Right: a [panel colour] side panel with a title "[part name]", two lines of body text, a small
"Source: [source]" line, and a list of [n] part names. Top of panel: three pill buttons
"Exploded view", "Quiz mode", "Reset". Flat design, [palette as colour names], generous spacing,
light sans-serif typography, no device frame, no watermark, legible placeholder text.

Plus a negative prompt (cluttered UI, tiny text, neon colours, photorealistic hands, watermarks) and two variants: one for phone in portrait, one for dark mode.

3. Handover notes

What the next steps need from this brief: the parts list it implies (for model-prompt-pack) and the palette and layout values (for explorer-viewer-builder), as a short table.

Quality Checks

  • Learning outcomes are three to five and each starts with a verb
  • Every interaction has a keyboard path, including selecting parts
  • Every palette text pair is stated with a contrast of at least 4.5:1
  • Layout is specified for both desktop and phone
  • The image prompt names device, aspect, palette and every panel element
  • The brief requires a named source for every label and calls the model illustrative
  • The handover table lists the parts list and palette values

Anti-Patterns

  • Labels floating over the model. They collide and become unreadable when the model rotates; use a side panel.
  • Beautiful but unteachable. A brief with no learning outcomes produces a toy.
  • Mouse-only selection. Keyboard and screen-reader users need the parts list.
  • Mocks with unreadable text. Ask for legible placeholder text, or the mock misleads reviewers.

Example Trigger Phrases

  • "Design the interface for a 3D explorer of the human heart for GCSE students."
  • "Write an image prompt for a UI mock of an interactive jet engine viewer."
  • "Plan the screens for a museum touch-screen 3D model of a volcano."
  • "Brief for a 3D cell explorer app, phone first."

Frequently asked questions

What does the Explorer Interface Brief AI skill do?

Use when asked to design the interface for an interactive 3D explorer, plan a UI for exploring a 3D model of a topic, or write an image-model prompt for a 3D learning app mock-up. Produces, from a topic, the UI design brief (audience, layout, panels, interactions, label style, colour palette, accessibility) and an image-model prompt for the interface mock. First step of explorer-pipeline.

Why use Explorer Interface Brief on TypingMind?

Because you install it once and use it with any model. Explorer Interface Brief 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 Explorer Interface Brief in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mohitagw15856/pm-claude-skills/tree/main/plugins/pm-3d-explorer/skills/explorer-interface-brief. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Explorer Interface Brief?

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 Explorer Interface Brief?

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

Is the Explorer Interface Brief AI skill free?

Yes. It is published on GitHub by mohitagw15856 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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