Microfrontends

Organization

vercel

microfrontends

Guide for building, configuring, and deploying microfrontends on Vercel. Use this skill when the user mentions microfrontends, multi-zones, splitting an app across teams, independent deployments, cross-app routing, incremental migration, composing multiple frontends under one domain, microfrontends.json, @vercel/microfrontends, the microfrontends local proxy, or path-based routing between Vercel projects. Also use when the user asks about shared layouts across projects, navigation between microfrontends, fallback environments, asset prefixes, or feature flag controlled routing.

Overview

Publisher	vercel
Repository	`vercel-plugin`
Skill name	`microfrontends`
Stars	286
Forks	56
Bundled files	6
Links	Skill source Repository Homepage

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.
6 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by vercel on GitHub. Read the source before you install it.

Installation

Install the Microfrontends AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/vercel/vercel-plugin.git /tmp/vercel-plugin
mkdir -p .claude/skills
cp -r /tmp/vercel-plugin/skills/microfrontends .claude/skills/microfrontends

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Microfrontends 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 Microfrontends 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 Microfrontends 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.

Vercel Microfrontends

Split a large application into independently deployable units that render as one cohesive app. Vercel handles routing on its global network using microfrontends.json.

Core concepts: default app (has microfrontends.json, serves unmatched requests) · child apps (have routing path patterns) · asset prefix (prevents static-asset collisions) · independent deployments.

Frameworks: Next.js (App Router + Pages Router), SvelteKit, React Router, Vite — all via @vercel/microfrontends.

CLI (vercel microfrontends / vercel mf):

create-group — create a new group; interactive by default, or fully non-interactive with --non-interactive (options: --name, --project (repeatable), --default-app, --default-route, --project-default-route (repeatable, format: <project>=<route>, required for each non-default project in non-interactive mode), --yes to skip confirmation prompt); note: --non-interactive is blocked if adding the projects would exceed the free tier limit — the user must confirm billing changes interactively
add-to-group — add the current project to an existing group; requires interactive terminal (options: --group, --default-route)
remove-from-group — remove the current project from its group; requires interactive terminal (option: --yes skips project-link prompt only)
delete-group — delete a group and all its settings, irreversible; requires interactive terminal (option: --group to pre-select group)
inspect-group — retrieve group metadata (project names, frameworks, git repos, root dirs); useful for automating setup (options: --group, --format=json, --config-file-name)
pull — pull remote microfrontends.json for local development (option: --dpl)
microfrontends proxy — local dev proxy · microfrontends port — print auto-assigned port

Finding Detailed Information

This skill includes detailed reference docs in the references/ directory. Do not read all references upfront. Instead, search or grep the relevant file when the user asks about a specific topic:

Topic	Reference file
Getting started, quickstart, framework setup, `microfrontends.json` schema, fields, naming, examples	`references/configuration.md`
Path expressions, asset prefixes, flag-controlled routing, middleware	`references/path-routing.md`
Local proxy setup, polyrepo config, Turborepo, ports, deployment protection	`references/local-development.md`
Inspecting groups (`inspect-group`), adding/removing projects, fallback environments, navigation, observability	`references/managing-microfrontends.md`
Testing utilities (`validateMiddlewareConfig`, `validateRouting`, etc.), debug headers, common issues	`references/troubleshooting.md`
Deployment protection, Vercel Firewall, WAF rules for microfrontends	`references/security.md`

When the user asks about a specific topic, use grep or search over the relevant reference file to find the answer without loading all references into context.

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 Microfrontends AI skill do?

Why use Microfrontends on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vercel/vercel-plugin/tree/main/skills/microfrontends. 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 Microfrontends?

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 Microfrontends?

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

Is the Microfrontends AI skill free?

It is published on GitHub by vercel. Check the repository for licensing terms. 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Vercel Microfrontends

Finding Detailed Information

Bundled files

Frequently asked questions

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