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Mobile Platform Guidelines

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Xinvtech
mobile-platform-guidelines

Apply and review iOS and Android native behavior rules across navigation, insets, permissions, system surfaces, accessibility, adaptive layouts, lifecycle, and platform-specific interaction. Use when Codex needs a platform decision, a cross-platform parity review, a guideline checklist, or a device-validation plan for mobile UX/UI.

Overview

PublisherXinvtech
Repositorymobile-design-os
Skill namemobile-platform-guidelines
Stars
4
Forks
0
Bundled files
7
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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.

  • 7 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 Platform Guidelines 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-platform-guidelines
  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-platform-guidelines .claude/skills/mobile-platform-guidelines
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mobile Platform Guidelines 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 Platform Guidelines 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 Platform Guidelines 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 Platform Guidelines

Turn platform knowledge into explicit product decisions and testable checks. Preserve outcome parity while allowing implementation and interaction differences between iOS and Android.

Select the platform mode

  • iOS: use the iOS reference and check navigation, safe areas, Dynamic Type, VoiceOver, Reduce Motion, keyboard, permissions, and system surfaces.
  • Android: use the Android reference and check predictive Back, edge-to-edge insets, scalable text, TalkBack, adaptive layouts, process recreation, and Material/custom behavior.
  • Cross-platform: review shared user outcomes and record where behavior must diverge.

Read the existing first-party references before making a claim:

For products whose core value depends on device motion, audio, or haptics, also read sensor, audio, and haptic behavior. Treat hardware availability, permission, interruption, route change, and a visible non-sensor alternative as required product states.

Recheck the linked official documentation before version-specific claims. Record the documentation date, OS/version scope, and whether a conclusion is observed, derived, or not-tested.

Run the review

  1. Establish target OS versions, form factors, input modes, appearance, text-size settings, and relevant system integrations.
  2. Map each platform rule to a screen, state, flow, component, or system surface.
  3. Separate product outcome parity from implementation parity; do not force identical navigation or permission behavior.
  4. Mark each check pass, fail, not-tested, or not-applicable. A screenshot can support visible layout evidence but cannot prove runtime semantics.
  5. Give every failure an owner, workaround/fallback, and verification method.

Create:

Run python3 scripts/validate_platform_guidelines.py <path-to-platform-guidelines.json> and fix structural errors. Keep runtime checks untested until a device or executable prototype supplies evidence.

Enforce the output order

  1. Platform scope and source freshness.
  2. Outcome-parity contract.
  3. Rule/check matrix by platform and area.
  4. Fallbacks, risks, and device test plan.
  5. Decision, open questions, and confidence.

Do not label a design “native” from visual resemblance alone.

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 Platform Guidelines AI skill do?

Apply and review iOS and Android native behavior rules across navigation, insets, permissions, system surfaces, accessibility, adaptive layouts, lifecycle, and platform-specific interaction. Use when Codex needs a platform decision, a cross-platform parity review, a guideline checklist, or a device-validation plan for mobile UX/UI.

Why use Mobile Platform Guidelines on TypingMind?

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

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

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 Platform Guidelines?

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

Is the Mobile Platform Guidelines 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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