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Mobile Prototype

Community
Xinvtech
mobile-prototype

Turn mobile UX, wireframe, UI, and platform contracts into a testable interaction prototype plan, a standalone browser review runner, or an implementation handoff. Use when Codex needs navigation transitions, gestures, motion, feedback, failure injection, runtime test cases, or an executable prototype scope.

Overview

PublisherXinvtech
Repositorymobile-design-os
Skill namemobile-prototype
Stars
4
Forks
0
Bundled files
10
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.

  • 10 bundled files

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

  • Open source

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

Installation

Install the Mobile 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/Xinvtech/mobile-design-os/tree/main/skills/mobile-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/Xinvtech/mobile-design-os.git /tmp/mobile-design-os
mkdir -p .claude/skills
cp -r /tmp/mobile-design-os/skills/mobile-prototype .claude/skills/mobile-prototype
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mobile 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 Mobile 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 Mobile 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.

Mobile Prototype

Make the core task observable in motion and runtime. Treat a prototype as a behavior test surface, not as a collection of clickable pictures.

Choose the prototype target

  • Behavior prototype: define screens, states, transitions, feedback, interruption, and test cases for a tool such as Figma, ProtoPie, or a native prototype.
  • Browser review runner: render a self-contained HTML design prototype from prototype.json, a UI Design contract, and an optional Design System contract. The default URL is a clean product preview; append ?inspect=1 for state continuity, contract edges, and deterministic failure review before production implementation.
  • Executable spike: create or hand off a narrow runnable prototype with real text, persistence boundaries, platform surfaces, and deterministic failure hooks.
  • Validation pass: execute the prototype test matrix and record evidence, limitations, and regressions.

Prefer mobile-wireframe before this Skill and mobile-design-to-code when the user wants framework code. Preserve upstream Screen, State, Flow, Requirement, Token, and Component IDs.

Define the runtime contract

  1. Select one critical task and one high-risk recovery path.
  2. Map each screen/state node to its entry, exit, action, system response, and durable result.
  3. Define animation, gesture, haptic, sound, and announcement behavior with a reduced-motion and nonvisual equivalent.
  4. Add interruption, background/termination, offline, duplicate submission, permission denial, and destructive recovery where applicable.
  5. Define deterministic failure hooks for persistence, network, indexing, permission, and system-surface cases instead of relying on luck.
  6. Keep prototype status honest: a plan or static render is not runtime evidence.

Read references/prototype-rules.md and references/prototype-schema.md before creating structured output.

Produce and validate

Create:

Run python3 scripts/validate_prototype.py <path-to-prototype.json>. Use the resulting not-tested records to drive implementation and device QA; do not convert them to pass without evidence.

When the prototype follows UI Design, also run python3 scripts/validate_ui_prototype_alignment.py --ui-design <path-to-ui-design.json> --prototype <path-to-prototype.json>. This catches missing state nodes, unmapped explicit interactions, and high-risk states without a recovery hook.

For a clickable design-review surface, run the following after the contract checks. The supplied Design System must contain a locked visual direction copied from ui-design.json; an unlocked or legacy theme is a hard stop.

bash
python3 scripts/render_prototype_html.py \
  --ui-design <path-to-ui-design.json> \
  --design-system <path-to-design-system.json> \
  --prototype <path-to-prototype.json> \
  --output <output-dir>/prototype-runner/index.html
python3 scripts/validate_prototype_runner.py \
  --html <output-dir>/prototype-runner/index.html \
  --prototype <path-to-prototype.json>

The default runner URL must show only the product preview: no QA header, inspector, evidence badge, or debug phone chrome. The inspector remains available at ?inspect=1. The renderer must consume the locked visual fingerprint and semantic UI/Design System tokens for surface, text, action, border, typography, spacing, radius, color hierarchy, and module rhythm; do not reintroduce a generic card-stack, pill-button shell, or a legacy Margin theme. The runner must expose the product's primary task, state jump, outgoing contract edges, and deterministic failure switches for applicable persistence/index/permission/destructive paths in inspect mode. Its report remains runtimeEvidence: not-tested until browser, accessibility, interruption, and device evidence exists. A browser runner is a UI/prototype artifact, not production Flutter code.

Enforce the output order

  1. Prototype scope and evidence status.
  2. Screen/state nodes and transitions.
  3. Feedback, motion, gesture, system-surface, and interruption rules.
  4. Failure hooks and test matrix.
  5. Implementation handoff, evidence, and open risks.

Do not finish with a happy-path click-through that cannot show recovery, state continuity, accessibility pressure, or system behavior.

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 Mobile Prototype AI skill do?

Turn mobile UX, wireframe, UI, and platform contracts into a testable interaction prototype plan, a standalone browser review runner, or an implementation handoff. Use when Codex needs navigation transitions, gestures, motion, feedback, failure injection, runtime test cases, or an executable prototype scope.

Why use Mobile Prototype on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Xinvtech/mobile-design-os/tree/main/skills/mobile-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 Mobile 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 Mobile Prototype?

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

Is the Mobile Prototype AI skill free?

Yes. It is published on GitHub by Xinvtech 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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