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Native Feel Cross Platform Desktop

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yetone
native-feel-cross-platform-desktop

Use when the user is designing, prototyping, or rewriting a desktop app that must run on multiple OSes (macOS + Windows, optionally Linux) AND feel indistinguishable from a native app to its users — fast launch, native windowing, native input handling, native materials. Trigger words include "cross-platform desktop", "Electron alternative", "Tauri vs native", "WebView wrapper", "near-native performance", "Raycast architecture", "WebKit/WebView2 quirks", "WKWebView", "system tray app", "global hotkey app", "launcher app". Do NOT trigger this skill for pure web apps, pure mobile apps, or for greenfield projects that have no native-feel requirement.

Overview

Publisheryetone
Repositorynative-feel-skill
Skill namenative-feel-cross-platform-desktop
Stars
1.9K
Forks
76
Bundled files
9
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.

  • 9 bundled files

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

  • Open source

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

Installation

Install the Native Feel Cross Platform Desktop 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/yetone/native-feel-skill.git \
  .claude/skills/native-feel-cross-platform-desktop
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Native Feel Cross Platform Desktop 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 Native Feel Cross Platform Desktop 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 Native Feel Cross Platform Desktop 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.

Native-Feel Cross-Platform Desktop

You are advising on the architecture of a cross-platform desktop app that must feel native. This skill captures the philosophy, architecture, and concrete pitfalls — distilled from Raycast's public technical deep-dive on their 2.0 rewrite and verified by reverse-engineering the shipping Raycast Beta.app binary on macOS.

How to use this skill

  1. Start with the philosophy in references/01-philosophy.md. It frames the central tension this architecture resolves — how to get cross-platform DX and near-native performance at the same time — and gives you eight tenets that name the structural moves. Every concrete decision later flows from one of those tenets. If the user is making a decision that contradicts a tenet, surface the tenet by number and short name and explain the trade-off.
  2. Match the user's question to a reference file. Don't dump the whole skill — load only what's needed:
    • Architecture / "which layers should I have?" → references/02-architecture.md
    • "Why does my WebView flicker / stutter / freeze when hidden?" → references/03-webview-survival.md (the highest-density file — every item is a real bug with a real fix)
    • "How do I type my IPC across Rust/Swift/C#/TS?" → references/04-ipc-contract.md
    • "Why does Activity Monitor say 400 MB?" → references/05-memory-truths.md
    • "How do I make it not feel like a webpage?" → references/06-native-conventions.md
    • "What does Raycast actually ship?" (concrete evidence) → references/07-evidence-raycast.md
  3. Before recommending an architecture, run the decision tree in checklists/decision-tree.md. It rules this stack OUT for several common project shapes — say so directly.
  4. Before the user claims their app "feels native", run checklists/ship-readiness.md. It's a 30-item audit; most apps fail 5–10 items on first pass.

The one-paragraph version

A native-feel cross-platform desktop app is not a web app with native hooks and not Electron with a custom theme. It is a native shell (Swift/AppKit on macOS, C#/WPF on Windows) that owns the window, the hotkeys, the menu bar, the materials, and the lifecycle — and embeds the system WebView (WKWebView or WebView2) purely as a rendering surface for a shared React/TypeScript UI. Business logic lives in a long-lived Node process bundled with the app. Performance-critical subsystems (file indexing, calculation, crypto) live in Rust, shared across platforms and exposed through UniFFI-generated typed bindings. Four runtimes communicate through a single declared interface that generates typed clients for each side. The whole thing fits in ~400 MB resident memory, of which ~150 MB is the inescapable WebView+Node baseline. You pay that baseline so that one React codebase serves both OSes; you earn it back through hot-reload iteration speed and a shared extension API that already runs thousands of community plugins on both platforms.

Core anti-patterns to call out immediately

When you see the user doing any of these, stop and ask:

  • "Let's just use Electron and theme it" → Electron abstracts away the system WebView, window class, and material APIs you need for native feel. You cannot get Liquid Glass / acrylic / true vibrancy through Electron's abstraction without forking it. Recommend references/02-architecture.md instead.
  • "Let's use Tauri — it's like Electron but lighter" → Tauri ships its own WebView wrapper and abstracts platform APIs. Same control-loss problem as Electron, plus less mature. Acceptable for utilities; not for apps where every window animation has to match the OS.
  • "Let's render UI in Swift/C# and share business logic" → You will maintain two UI codebases forever. Every feature ships twice. Designers maintain two specs. Recommend WebView-as-renderer instead.
  • "WebKit is throttling us; let's spin our own polling loop" → No. The throttling is solvable with two specific WKWebView configuration flags. See references/03-webview-survival.md § "Hidden window throttling".
  • "Memory is bad — we're at 400 MB" → Probably wrong measurement. Activity Monitor double-counts shared frameworks and treats compressed pages as resident. See references/05-memory-truths.md before optimizing anything.
  • "Let's hand-write the IPC types in each language" → They will drift within a sprint. Use UniFFI (for Rust ↔ Swift/Kotlin/C#) or hand-roll a single IDL that generates clients. See references/04-ipc-contract.md.
  • "Adding cursor: pointer to make it feel responsive" → That's exactly what makes it feel web. Native UIs do not change the cursor on hoverable rows. See references/06-native-conventions.md.

Output style

When advising:

  • Quote the specific tenet from references/01-philosophy.md that applies (e.g., "T3 — adopt the platform; don't compete with it: the OS draws blur better than you can").
  • Cite the file and section, not the whole skill.
  • For each recommendation, name what the user is giving up in exchange. There are no free wins in this architecture — the whole skill is about deliberate trade-offs.
  • If you're unsure whether the user's project should even use this architecture, run them through checklists/decision-tree.md before giving advice. It is okay to conclude "this skill doesn't apply — build a normal Electron app."

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 Native Feel Cross Platform Desktop AI skill do?

Use when the user is designing, prototyping, or rewriting a desktop app that must run on multiple OSes (macOS + Windows, optionally Linux) AND feel indistinguishable from a native app to its users — fast launch, native windowing, native input handling, native materials. Trigger words include "cross-platform desktop", "Electron alternative", "Tauri vs native", "WebView wrapper", "near-native performance", "Raycast architecture", "WebKit/WebView2 quirks", "WKWebView", "system tray app", "global hotkey app", "launcher app". Do NOT trigger this skill for pure web apps, pure mobile apps, or for...

Why use Native Feel Cross Platform Desktop on TypingMind?

Because you install it once and use it with any model. Native Feel Cross Platform Desktop 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 Native Feel Cross Platform Desktop in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yetone/native-feel-skill/tree/master. 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 Native Feel Cross Platform Desktop?

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 Native Feel Cross Platform Desktop?

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

Is the Native Feel Cross Platform Desktop AI skill free?

Yes. It is published on GitHub by yetone 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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