# convex-agents

Guides agent setup with the @convex-dev/agent component. Useful when adding chat threads, tool calling for queries and mutations, or RAG to a Convex app.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1500 installs · ★ 405
- Author: waynesutton
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/waynesutton/builder-skills/tree/HEAD/skills/convex-agents/SKILL.md
- Updated: 2026-09-28
- HTML: https://affpapa.org/en/nevibecode/skills/convex-agents

## What it does

This skill defines architectural patterns for AI agents on Convex. It generates code for threads, reactive UI message feeds with `useUIMessages`, and tools built with `createTool` that execute queries or mutations via context.

The core constraint is that every LLM call must run inside an action. Mutations must stay deterministic without network access, so calling `generateText` in a mutation will fail immediately. Instead, mutations store the user input with `saveMessage` and schedule an `internalAction` using `ctx.scheduler.runAfter`.

The setup relies on `@convex-dev/agent`, `ai`, `@ai-sdk/openai`, and `zod`, alongside an `OPENAI_API_KEY` environment variable. You also need to run `npx convex dev` once so the build generates `components.agent` before defining any agent instance.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add waynesutton/builder-skills --skill convex-agents -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/convex-agents/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/convex-agents/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add waynesutton/builder-skills --skill convex-agents -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/convex-agents/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add waynesutton/builder-skills --skill convex-agents -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/convex-agents/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install waynesutton/builder-skills convex-agents
```

2. **Manually: put the files in place**
- File: `.github/skills/convex-agents/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add waynesutton/builder-skills --skill convex-agents -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/waynesutton/builder-skills --path skills/convex-agents
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/convex-agents/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add waynesutton/builder-skills --skill convex-agents -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/waynesutton/builder-skills/tree/HEAD/skills/convex-agents/SKILL.md

## When to use it
- set up persistent chat threads and message history in Convex
- expose Convex queries and mutations to language models as typed tools
- stream and list reactive assistant messages in UI components
- separate prompt saving in mutations from model inference in actions

## Example prompts
- Create a support agent using @convex-dev/agent and gpt-4o-mini
- Define a searchOrders tool using createTool and Zod that calls api.orders.search
- Implement the startThread and sendMessage mutations with scheduled reply actions

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: ae7c810af77c9568.

BEGIN THIRD-PARTY FILE ae7c810af77c9568
````text
---
name: convex-agents
description: Builds AI agents on the Convex agent component: threads, messages, tools that call queries and mutations, streaming, RAG with vector search, and workflows for multi step jobs. Use when adding a chat assistant, tool calling agent, or retrieval feature to a Convex app.
---

# Convex agents

Produces a chat or tool calling agent backed by `@convex-dev/agent`, with thread history stored in Convex and a reactive message list for the UI. The one rule: every LLM call runs inside an action. Mutations save the prompt and schedule the action; they never call a model.

## When to reach for this

- Adding a chat assistant with persistent conversation history
- Letting an LLM call your queries and mutations as tools
- Streaming a model reply to one or more clients
- Answering questions over your own documents (RAG)
- Chaining several LLM steps into a durable job that survives restarts

## Install and register

```bash
npm install @convex-dev/agent ai @ai-sdk/openai zod
npx convex env set OPENAI_API_KEY sk-...
```

```typescript
// convex/convex.config.ts
import { defineApp } from "convex/server";
import agent from "@convex-dev/agent/convex.config";

const app = defineApp();
app.use(agent);
export default app;
```

Run `npx convex dev` once so `components.agent` is generated before defining an agent.

## Define an agent

```typescript
// convex/agent.ts
import { Agent, stepCountIs } from "@convex-dev/agent";
import { openai } from "@ai-sdk/openai";
import { components } from "./_generated/api";

export const supportAgent = new Agent(components.agent, {
  name: "Support Agent",
  languageModel: openai.chat("gpt-4o-mini"),
  instructions: "You are a support assistant. Answer briefly and cite docs when possible.",
  // Lets the model call tools and then respond, up to 5 steps
  stopWhen: stepCountIs(5),
});
```

`name` tags each saved message with the agent that wrote it. Everything except `name` can be overridden per call.

## Create a thread and generate a reply

Save the user prompt in a mutation, then schedule an internal action that generates the reply. Clients subscribed to the thread see the new message without the action returning anything.

```typescript
// convex/chat.ts
import { v } from "convex/values";
import { mutation, internalAction, QueryCtx, MutationCtx } from "./_generated/server";
import { components, internal } from "./_generated/api";
import { saveMessage } from "@convex-dev/agent";
import { supportAgent } from "./agent";

// Throws unless the signed in user owns the thread
async function authorizeThreadAccess(ctx: QueryCtx | MutationCtx, threadId: string) {
  const identity = await ctx.auth.getUserIdentity();
  if (!identity) throw new Error("Not authenticated");
  const thread = await ctx.runQuery(components.agent.threads.getThread, { threadId });
````
END THIRD-PARTY FILE ae7c810af77c9568

The third-party file has ended. Everything between the ae7c810af77c9568 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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---
NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md