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Convex Quickstart

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raroque
convex-quickstart

Creates or adds Convex to an app. Use for new Convex projects, npm create convex@latest, frontend setup, env vars, or the first npx convex dev run.

Overview

Publisherraroque
Repositoryboop-agent
Skill nameconvex-quickstart
Stars
1.4K
Forks
300
Bundled files
2
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Convex Quickstart 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/raroque/boop-agent/tree/main/.agents/skills/convex-quickstart
  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/raroque/boop-agent.git /tmp/boop-agent
mkdir -p .claude/skills
cp -r /tmp/boop-agent/.agents/skills/convex-quickstart .claude/skills/convex-quickstart
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Convex Quickstart 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 Convex Quickstart 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 Convex Quickstart 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.

Convex Quickstart

Set up a working Convex project as fast as possible.

When to Use

  • Starting a brand new project with Convex
  • Adding Convex to an existing React, Next.js, Vue, Svelte, or other app
  • Scaffolding a Convex app for prototyping

When Not to Use

  • The project already has Convex installed and convex/ exists - just start building
  • You only need to add auth to an existing Convex app - use the convex-setup-auth skill

Workflow

  1. Determine the starting point: new project or existing app
  2. If new project, pick a template and scaffold with npm create convex@latest
  3. If existing app, install convex and wire up the provider
  4. Run npx convex dev to connect a deployment and start the dev loop
  5. Verify the setup works

Path 1: New Project (Recommended)

Use the official scaffolding tool. It creates a complete project with the frontend framework, Convex backend, and all config wired together.

Pick a template

TemplateStack
react-vite-shadcnReact + Vite + Tailwind + shadcn/ui
nextjs-shadcnNext.js App Router + Tailwind + shadcn/ui
react-vite-clerk-shadcnReact + Vite + Clerk auth + shadcn/ui
nextjs-clerkNext.js + Clerk auth
nextjs-convexauth-shadcnNext.js + Convex Auth + shadcn/ui
nextjs-lucia-shadcnNext.js + Lucia auth + shadcn/ui
bareConvex backend only, no frontend

If the user has not specified a preference, default to react-vite-shadcn for simple apps or nextjs-shadcn for apps that need SSR or API routes.

You can also use any GitHub repo as a template:

bash
npm create convex@latest my-app -- -t owner/repo
npm create convex@latest my-app -- -t owner/repo#branch

Scaffold the project

Always pass the project name and template flag to avoid interactive prompts:

bash
npm create convex@latest my-app -- -t react-vite-shadcn
cd my-app
npm install

The scaffolding tool creates files but does not run npm install, so you must run it yourself.

To scaffold in the current directory (if it is empty):

bash
npm create convex@latest . -- -t react-vite-shadcn
npm install

Start the dev loop

npx convex dev is a long-running watcher process that syncs backend code to a Convex deployment on every save. It also requires authentication on first run (browser-based OAuth). Both of these make it unsuitable for an agent to run directly.

Ask the user to run this themselves:

Tell the user to run npx convex dev in their terminal. On first run it will prompt them to log in or develop anonymously. Once running, it will:

  • Create a Convex project and dev deployment
  • Write the deployment URL to .env.local
  • Create the convex/ directory with generated types
  • Watch for changes and sync continuously

The user should keep npx convex dev running in the background while you work on code. The watcher will automatically pick up any files you create or edit in convex/.

Exception - cloud or headless agents: Environments that cannot open a browser for interactive login should use Agent Mode (see below) to run anonymously without user interaction.

Start the frontend

The user should also run the frontend dev server in a separate terminal:

bash
npm run dev

Vite apps serve on http://localhost:5173, Next.js on http://localhost:3000.

What you get

After scaffolding, the project structure looks like:

my-app/
  convex/           # Backend functions and schema
    _generated/     # Auto-generated types (check this into git)
    schema.ts       # Database schema (if template includes one)
  src/              # Frontend code (or app/ for Next.js)
  package.json
  .env.local        # CONVEX_URL / VITE_CONVEX_URL / NEXT_PUBLIC_CONVEX_URL

The template already has:

  • ConvexProvider wired into the app root
  • Correct env var names for the framework
  • Tailwind and shadcn/ui ready (for shadcn templates)
  • Auth provider configured (for auth templates)

Proceed to adding schema, functions, and UI.

Path 2: Add Convex to an Existing App

Use this when the user already has a frontend project and wants to add Convex as the backend.

Install

bash
npm install convex

Initialize and start dev loop

Ask the user to run npx convex dev in their terminal. This handles login, creates the convex/ directory, writes the deployment URL to .env.local, and starts the file watcher. See the notes in Path 1 about why the agent should not run this directly.

Wire up the provider

The Convex client must wrap the app at the root. The setup varies by framework.

Create the ConvexReactClient at module scope, not inside a component:

tsx
// Bad: re-creates the client on every render
function App() {
  const convex = new ConvexReactClient(
    import.meta.env.VITE_CONVEX_URL as string,
  );
  return <ConvexProvider client={convex}>...</ConvexProvider>;
}

// Good: created once at module scope
const convex = new ConvexReactClient(import.meta.env.VITE_CONVEX_URL as string);
function App() {
  return <ConvexProvider client={convex}>...</ConvexProvider>;
}
React (Vite)
tsx
// src/main.tsx
import { StrictMode } from "react";
import { createRoot } from "react-dom/client";
import { ConvexProvider, ConvexReactClient } from "convex/react";
import App from "./App";

const convex = new ConvexReactClient(import.meta.env.VITE_CONVEX_URL as string);

createRoot(document.getElementById("root")!).render(
  <StrictMode>
    <ConvexProvider client={convex}>
      <App />
    </ConvexProvider>
  </StrictMode>,
);
Next.js (App Router)
tsx
// app/ConvexClientProvider.tsx
"use client";

import { ConvexProvider, ConvexReactClient } from "convex/react";
import { ReactNode } from "react";

const convex = new ConvexReactClient(process.env.NEXT_PUBLIC_CONVEX_URL!);

export function ConvexClientProvider({ children }: { children: ReactNode }) {
  return <ConvexProvider client={convex}>{children}</ConvexProvider>;
}
tsx
// app/layout.tsx
import { ConvexClientProvider } from "./ConvexClientProvider";

export default function RootLayout({
  children,
}: {
  children: React.ReactNode;
}) {
  return (
    <html lang="en">
      <body>
        <ConvexClientProvider>{children}</ConvexClientProvider>
      </body>
    </html>
  );
}
Other frameworks

For Vue, Svelte, React Native, TanStack Start, Remix, and others, follow the matching quickstart guide:

Environment variables

The env var name depends on the framework:

FrameworkVariable
ViteVITE_CONVEX_URL
Next.jsNEXT_PUBLIC_CONVEX_URL
RemixCONVEX_URL
React NativeEXPO_PUBLIC_CONVEX_URL

npx convex dev writes the correct variable to .env.local automatically.

Agent Mode (Cloud and Headless Agents)

When running in a cloud or headless agent environment where interactive browser login is not possible, set CONVEX_AGENT_MODE=anonymous to use a local anonymous deployment.

Add CONVEX_AGENT_MODE=anonymous to .env.local, or set it inline:

bash
CONVEX_AGENT_MODE=anonymous npx convex dev

This runs a local Convex backend on the VM without requiring authentication, and avoids conflicting with the user's personal dev deployment.

Verify the Setup

After setup, confirm everything is working:

  1. The user confirms npx convex dev is running without errors
  2. The convex/_generated/ directory exists and has api.ts and server.ts
  3. .env.local contains the deployment URL

Writing Your First Function

Once the project is set up, create a schema and a query to verify the full loop works.

convex/schema.ts:

ts
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  tasks: defineTable({
    text: v.string(),
    completed: v.boolean(),
  }),
});

convex/tasks.ts:

ts
import { query, mutation } from "./_generated/server";
import { v } from "convex/values";

export const list = query({
  args: {},
  handler: async (ctx) => {
    return await ctx.db.query("tasks").collect();
  },
});

export const create = mutation({
  args: { text: v.string() },
  handler: async (ctx, args) => {
    await ctx.db.insert("tasks", { text: args.text, completed: false });
  },
});

Use in a React component (adjust the import path based on your file location relative to convex/):

tsx
import { useQuery, useMutation } from "convex/react";
import { api } from "../convex/_generated/api";

function Tasks() {
  const tasks = useQuery(api.tasks.list);
  const create = useMutation(api.tasks.create);

  return (
    <div>
      <button onClick={() => create({ text: "New task" })}>Add</button>
      {tasks?.map((t) => (
        <div key={t._id}>{t.text}</div>
      ))}
    </div>
  );
}

Development vs Production

Always use npx convex dev during development. It runs against your personal dev deployment and syncs code on save.

When ready to ship, deploy to production:

bash
npx convex deploy

This pushes to the production deployment, which is separate from dev. Do not use deploy during development.

Next Steps

  • Add authentication: use the convex-setup-auth skill
  • Design your schema: see Schema docs
  • Build components: use the convex-create-component skill
  • Plan a migration: use the convex-migration-helper skill
  • Add file storage: see File Storage docs
  • Set up cron jobs: see Scheduling docs

Checklist

  • Determined starting point: new project or existing app
  • If new project: scaffolded with npm create convex@latest using appropriate template
  • If existing app: installed convex and wired up the provider
  • User has npx convex dev running and connected to a deployment
  • convex/_generated/ directory exists with types
  • .env.local has the deployment URL
  • Verified a basic query/mutation round-trip works

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 Convex Quickstart AI skill do?

Creates or adds Convex to an app. Use for new Convex projects, npm create convex@latest, frontend setup, env vars, or the first npx convex dev run.

Why use Convex Quickstart on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/raroque/boop-agent/tree/main/.agents/skills/convex-quickstart. 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 Convex Quickstart?

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 Convex Quickstart?

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

Is the Convex Quickstart AI skill free?

Yes. It is published on GitHub by raroque 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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