architecture to frontend scaffold

    2

    Scaffold and verify runnable frontend architectures with enforced module boundaries and mocked data layers.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurfMManus+14 more

    See it in action

    You say

    Scaffold a new React monorepo using Feature-Sliced Design. I need a shared UI library and a 'dashboard' app with mocked user statistics. Verify it builds and starts.

    Your agent does

    Plan generated for FSD monorepo. Created /packages/ui and /apps/dashboard. Defined boundaries for entities, features, and widgets. Installed deps, ran npm run build, and verified dev server at localhost:3000. Mocked userService implemented with 200ms latency. Architecture report saved.

    What you get

    Generate buildable frontend skeletons from architectural descriptions.Enforce strict boundary rules between UI, domain, and data layers.Automate dependency installation and dev server verification.Create decoupled mock data services for immediate UI prototyping.

    About this skill

    The problem

    Translating a conceptual frontend architecture into a working file structure and buildable skeleton is tedious. Developers often waste hours manually creating folders, configuring build tools, and setting up mock data boundaries before writing their first feature.

    What it does

    • Analyzes your architectural requirements including Atomic Design, FSD, or Micro Frontends.
    • Generates a complete TypeScript frontend skeleton with strictly defined module boundaries and public APIs.
    • Implements a typed, asynchronous mock data layer to decouple UI from future backend integration.
    • Automates the "first boot" by installing dependencies, running production builds, and verifying the dev server.
    • Produces a detailed architecture report mapping your requirements to the generated codebase.

    Frameworks & tools

    TypeScript, Node.js, and standard frontend toolchains. Supports Monorepos, Micro Frontends, and major package managers.

    Why this beats prompting it yourself

    Generic prompts often result in a messy pile of files that don't respect architectural boundaries or fail to build. This skill follows a rigorous verification playbook, booting a real server to fix errors and ensure the scaffold is actually runnable before handing it over.

    Use cases

    • Bootstrapping a new FSD-compliant React project with pre-configured domain modules.
    • Prototyping a micro-frontend composition to test package boundaries.
    • Setting up a clean lab environment for UI component development with mocked data services.
    • Migrating a flat folder structure into a multi-layered Atomic Design system.

    Known limitations

    Requires Claude Code and Node.js environment. Does not silently install global system tools.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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