> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fetchhive.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Creating and Editing

> Create a prompt, add messages, manage inputs, and test it in the prompt editor

Use the prompt editor to write a standalone prompt, pass test inputs, and check the response before you create a prompt deployment.

## Overview

You start in the **Prompts** list, create a prompt, and open the editor. From there, you can add messages, work with prompt inputs, adjust editor settings, and click **Run** to test the prompt inside the dashboard.

The in-editor **Run** action is for testing. It is separate from calling a prompt through the public API.

## How do I create a prompt? <a href="#create-prompt" id="create-prompt" />

Open **Prompts** in the sidebar.

Click **Create Prompt**.

Enter a name for the prompt. If your workspace uses categories, you can also choose a category before you save.

Click **Create Prompt** again to open the prompt editor.

## How do I add and edit prompt messages? <a href="#add-edit-messages" id="add-edit-messages" />

Open the prompt in the editor.

In the prompt configuration area, click **Add Message**.

Choose the message content you want the model to receive. Keep the instructions short and direct when you're testing a new prompt.

Edit existing messages in the same prompt area until the prompt behaves the way you want.

If you want the prompt to accept dynamic values, add variables in your message content using the same variable format used elsewhere in the editor, such as `{{text}}`.

For vision-capable models, `user` messages can also include an image URL. Click the image icon on the message and paste a public image URL.

## How do I work with inputs? <a href="#work-with-inputs" id="work-with-inputs" />

When your messages include variables, click **Inputs** in the editor header.

Use the input values sheet to enter test values for each variable used by the prompt.

Update the values any time you want to test a different input without changing the prompt messages themselves.

These input values are for editor testing. They help you run the prompt with realistic sample data before you create a prompt deployment.

## How do I test a prompt in the editor? <a href="#test-in-editor" id="test-in-editor" />

After you add your messages and any input values, click **Run**.

Fetch Hive sends the current prompt configuration to the model and shows the result in the response area of the editor.

Use this step to check the output before you save a version or create a prompt deployment. If the result is not what you want, update the messages or inputs and run it again.

## What else can I configure in the prompt editor? <a href="#prompt-editor-config" id="prompt-editor-config" />

The prompt editor includes additional configuration areas beyond the message list. Depending on the prompt and provider, you may see model settings, response format controls, tools, evaluations, and other editor options.

If a saved prompt uses a retired model, the editor shows a model warning and test runs are blocked with `model_deprecated`. Choose a current model before running or publishing the prompt again.

For Anthropic Claude models, the model parameters include **Prompt Cache**. Leave it **Disabled** for normal one-off runs, choose **5 minutes** for repeated runs that reuse the same prompt context in a short window, or choose **1 hour** when follow-up calls may happen after a longer pause. Fetch Hive applies this as Anthropic prompt caching on stable prompt prefixes only.

Use these controls when you need to refine how the prompt runs in the editor.

See also: [Publishing and Versioning](./publishing-and-versioning) and [Run with API](./run-with-api)