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智能体 github.blog · @Kayla Cinnamon

GitHub Copilot app 入门:用 canvas 构建自定义工作流

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GitHub 官方博客介绍 Copilot app 中的 canvas(画布扩展)功能:用户无需编码,只需在 agent 会话中输入 /create-canvas 并用自然语言描述所需工作流、界面操作和 agent 权限,agent 即生成看板、问题分诊板、发布清单、仪表盘或表单等界面,并在右侧面板打开。canvas 是双向的,agent 和用户可同时更新共享状态,无需额外发送或同步步骤;创建后可保存为项目扩展供团队共享,或保存为个人扩展。

AI推荐理由 GitHub 官方博客介绍 Copilot app 的 canvas 功能:用户用自然语言描述工作流,agent 生成可双向交互的界面(看板、清单、仪表盘等),并保存为可复用扩展。这是官方对具体产品能力的说明,信息密度较高,给出了 /create-canvas 的用法和协作机制。局限在于属于入门教程性质,未提供性能数据或独立验证,实际效果仍需用户自行验证。

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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. Try using the GitHub Copilot app > The post GitHub Copilot app for Beginners: How to build custom workflows with canvases appeared first on The GitHub Blog.

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