大多数工具会提供一套固定的屏幕界面，并要求你将工作适配其中。但如果你可以从自己期望的工作流出发，让界面围绕其构建，那会怎样？

这正是 GitHub Copilot 应用中“画布（canvases）”背后的理念。画布，也称为画布扩展，是一个你和智能体共享的可定制界面。它可以是看板、问题分类板、发布检查清单、仪表板、表单，甚至是电子表格：一种根据你的工作方式量身定制的用户界面。

由于画布支持双向交互，智能体可以在工作过程中更新它，你也可以通过按钮、卡片、过滤器和其他控件来做出更改。就像使用实时共享白板一样。

让我们来创建一个。

使用 /create-canvas 创建画布

要创建画布，你无需进行任何手工编码或设计。只需打开一个智能体会话，输入 /create-canvas 技能，并用自然英语描述你的需求。

确保你的提示词涵盖以下三个方面：

画布应支持的工作流。

你应在界面中能够执行的操作。

智能体应能够执行的操作。

例如，你可以输入：

/create-canvas Create a release notes canvas for tracking new feature work completed across GitHub Copilot app sessions. Include controls for reviewing and organizing entries and allow the agent to add and update them.

随后，智能体将构建界面并将其打开在右侧面板中，你无需编写文件或调整布局。只需一段描述，即可生成一个即插即用的自定义工具。

围绕你的工作流塑造画布

由于界面是根据你的描述生成的，你的第一个版本只是一个起点，你可以不断细化，直到满意为止。

你可以要求智能体添加一列或过滤器、拉取你当前的待合并请求（pull requests），或将整个画布转化为当天的检查清单。智能体会相应地修订画布以匹配你的需求。虽然没有固定的布局菜单可供选择，但只要你能够描述一个工作流，你就很可能将其转化为画布。

创建完成后，你的画布会保存为扩展程序，因此你可以再次使用它。你可以将其保留在项目中供团队共享，或将其保存为仅你个人使用的扩展程序。

即时协作，而非命令与等待

画布的真正力量在于你和智能体可以同时持续工作。

当你点击按钮、更新字段或移动卡片时，画布的共享状态会立即改变。智能体会看到相同的更新，无需单独的发送或同步步骤。

反之亦然。你可以要求智能体使用画布自身的能力——即你拥有的相同操作——来添加发布说明或移动卡片，然后观察这些更改在界面中显现。你不再需要发送命令并等待响应，而是与智能体共同引导工作进程。

带走这些要点

创建一个有用的画布始于三个简单的问题：

我希望看到什么信息？

我希望直接更改什么？

智能体应能够更新或执行什么操作？

不确定从哪里开始？社区已通过 Awesome Copilot 分享了现成的画布扩展程序，包括发布说明工具、看板、问题分类工作流等。安装一个接近你需求的扩展程序，然后要求智能体以与你自定义自己创建的画布相同的方式，将其调整以适应你的工作流。

从小处着手：打开一个会话，运行 /create-canvas ，并描述一个用于当前正在处理的事务的简单看板或检查清单。

作者：

高级 AI 开发者工具倡导者

Most tools give you a fixed set of screens and ask you to fit your work into them. But what if you could start with the workflow you want instead and have the interface take shape around it?

That’s the idea behind canvases in the GitHub Copilot app . A canvas, also called a canvas extension, is a customizable interface that you and the agent share. It can be a kanban board, an issue triage board, a release checklist, a dashboard, a form, or even a spreadsheet: a UI shaped to how you work.

Because the canvas is bidirectional, the agent can update it as it works, and you can use buttons, cards, filters, and other controls to make changes too. Just like using a live shared whiteboard.

Let’s create one.

Creating a canvas with /create-canvas

To create a canvas, you don’t have to do any coding or design by hand. Just open an agent session, enter the /create-canvas skill , and describe what you want in plain English.

Make sure your prompt covers three things:

The workflow the canvas should support.

What you should be able to do in the interface.

What the agent should be able to do.

For example, you could enter:

/create-canvas Create a release notes canvas for tracking new feature work completed across GitHub Copilot app sessions. Include controls for reviewing and organizing entries and allow the agent to add and update them.

Then, the agent will build the interface and open it in the right-side panel without you having to write files or mess with the layout. One description becomes a custom tool that’s ready to use.

Shaping the canvas around your workflow

Because the interface is generated from your description, your first version is just a starting point, and you can keep refining until you’re happy.

You could ask the agent to add a column or filter, pull in your open pull requests, or turn the entire canvas into a checklist for your day. The agent will revise the canvas to match. While there isn’t a fixed menu of layouts, if you can describe a workflow, you can likely turn it into a canvas.

Once created, your canvas is saved as an extension, so you can use it again. You can keep it with the project for your team to share or save it as a personal extension just for you.

Instant collaboration, not command and wait

The real power of a canvas is that you and the agent can both keep working at the same time.

When you click a button, update a field, or move a card, the canvas’ shared state changes immediately. The agent sees the same update without a separate send or sync step.

It works the other way, too. You can ask the agent to use the canvas’ own capabilities—the same actions available to you—to add a release note or move a card, then watch that change appear in the interface. Instead of sending a command and waiting for a response, you’re steering the work together.

Take this with you

Creating a useful canvas starts with three simple questions:

What information do I want to see?

What do I want to change directly?

What should the agent be able to update or do?

Not sure where to begin? The community has shared ready-made canvas extensions through Awesome Copilot , including release notes tools, kanban boards, issue triage workflows, and more. Install one that’s close to what you need, then ask the agent to customize it for your workflow in the same way you would refine a canvas you created yourself.

Start small: open a session, run /create-canvas , and describe a simple board or checklist for something you’re working on now.

Written by

Senior AI Developer Tools Advocate