# Agent Quick Start

By the end of this guide, you'll have an agent configured in the dashboard, tested in chat, and ready to call through the public API.

## Prerequisites

* A Fetch Hive workspace
* A workspace API key if you want to run the public cURL example - see [API Keys](/your-workspace/api-keys.md)

## Step 1: Create an agent

Open **Agents** in the sidebar, then click **Add Agent**.

Enter a **Name**. If your workspace uses categories, you can also choose a **Category**. Click **Save** to open the agent editor.

## Step 2: Configure the root agent

In the editor, click the root agent node to open **Agent Settings**.

Add a short **Instruction Prompt** that tells the agent what to do. You can also confirm the **Model**, but you can keep the default settings for this first pass.

For example:

```
You are a research assistant. Answer clearly and keep responses brief unless the user asks for more detail.
```

## Step 3: Test the agent in chat

Click **Chat** in the editor header.

Send a short test message in the chat panel and confirm that the agent responds the way you expect.

This chat panel is for dashboard testing. The UI explicitly says these messages are not saved, so treat it as a safe place to iterate on behavior before you wire the agent into your app.

## Step 4: Copy the public invoke snippet

Open **Code Snippet** in the editor header, or use **More** in the sidebar and click **Get Code**.

Select your **Agent** and **API Key**. The dialog shows the public cURL example for `POST /v1/agent/invoke`.

The dialog provides a cURL snippet here. The **Python** and **TypeScript** tabs are still marked **Coming Soon**.

```bash
curl 'https://api.fetchhive.com/v1/agent/invoke' \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json' \
  --data-raw '{
    "agent": "YOUR_AGENT_ID",
    "message": "Summarize the latest AI infrastructure trends",
    "streaming": true
  }' \
  --compressed
```

Replace `YOUR_API_KEY` and `YOUR_AGENT_ID` with your real values.

The in-app **Chat** panel uses a private dashboard testing flow. The snippet above is the public API flow you use outside the dashboard.

## Next steps

* [Agents](/api-reference/agents.md)
* [Creating and Configuring](/agents/creating-and-configuring.md)
* [Testing with Chat](/agents/testing-with-chat.md)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.fetchhive.com/getting-started/agent-quick-start.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.