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Skill Studio

A lightweight, cross-platform desktop app for building a modern AI skills manager.

Skill Studio is a Tauri-based desktop foundation for managing AI skills with a cleaner architecture, a better UX baseline, and a stronger separation between installation, activation, backup, sync, and diagnostics.

It is designed as an improved standalone successor to the skills management experience explored from the cc-switch project.

Highlights

  • Lightweight desktop stack powered by Tauri 2 + Rust
  • Modern frontend with React 19, TypeScript, Vite, Tailwind CSS v4, and React Query
  • Cross-platform architecture for macOS / Windows / Linux evolution
  • Modular backend boundaries for manifest, installer, sync, backup, and diagnostics
  • Polished dashboard scaffold with Installed / Sources / Backups / Settings starter pages
  • GitHub-ready project structure for iterating toward a production desktop app

Screenshot / UI Status

Current repository version includes:

  • Desktop shell layout
  • Hash-router based navigation
  • Feature placeholder pages
  • Tauri command examples (ping, get_app_overview)
  • Buildable frontend and Rust scaffold

This repository is currently a polished scaffold / architecture baseline, not the final fully featured product.

Tech Stack

Frontend

  • React 19
  • TypeScript
  • Vite
  • Tailwind CSS v4
  • React Router
  • React Query
  • Lucide React

Desktop / Backend

  • Tauri 2
  • Rust
  • tauri-plugin-log

Why this project exists

The goal is not just to recreate an existing skills manager, but to build a better one with clearer domain boundaries.

Planned separation includes:

  • Skill Source: repository / ZIP / local import origin
  • Skill Manifest: normalized metadata contract
  • Installed Skill: workspace-owned installed entity
  • Activation / Deployment: per-app enable / disable state and sync strategy
  • Backup / Restore: explicit lifecycle support instead of hidden side-effects
  • Diagnostics: drift detection, broken links, invalid states, and health reporting

Quick Start

Prerequisites

Make sure your environment has:

  • Node.js
  • npm
  • Rust toolchain
  • Tauri development prerequisites for your OS

Run locally

git clone git@github.com:cikichen/skill-studio.git
cd skill-studio
npm install
npm run tauri dev

Build frontend

npm run build

Build Rust backend

cd src-tauri
cargo build

Project Structure

src/
  app/                 App router entry
  features/
    skills/            Installed skills experience
    sources/           Sources & discovery management
    backups/           Backup / restore flow
    settings/          Application settings
  shared/
    components/        Layout shell and reusable UI blocks
    lib/               Tauri bridge helpers
    types/             Frontend domain types

src-tauri/src/
  commands/            Tauri invoke command layer
  core/
    manifest/          Manifest parsing contracts
    installer/         Install orchestration skeleton
    sync/              Deployment strategy skeleton
    backup/            Backup lifecycle skeleton
    diagnostics/       Health-check skeleton
  state.rs             Shared application state
  lib.rs               App bootstrap and command registration

Included in this scaffold

  • Dark polished dashboard shell
  • Installed / Sources / Backups / Settings starter pages
  • Hash Router based desktop navigation
  • React Query provider setup
  • Tauri command bridge examples
  • Rust module boundaries ready for real implementation
  • Project plan document: PROJECT-PLAN.md

Roadmap

Near term

  1. Define skill.json manifest schema
  2. Replace mock page data with real Tauri commands
  3. Add workspace discovery and target app detection
  4. Implement install / uninstall / enable / disable workflows
  5. Implement backup / restore / diagnostics flows

Later

  • ZIP import workflow
  • Repository discovery management
  • Unmanaged skill scan
  • Conflict detection and source resolution
  • Better component system in shadcn/ui style
  • Packaging, icons, metadata, and release automation

Development Notes

  • Routing currently uses Hash Router for desktop friendliness
  • Backend currently exposes example commands only
  • The current UI is a starter shell intended for rapid iteration
  • PROJECT-PLAN.md contains the implementation planning baseline

Repository

License

MIT

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