如今，大多数开发者都在与智能体协同工作，或者至少熟悉如何这样做。智能体帮助你探索想法并将其付诸行动，从规划项目到自动化工作流。很多时候，一次对话就足以推动你的工作向前迈进。
但那些不太适合对话模式的任务呢？
有些任务在你能够看到信息并与之交互时会更容易完成。你可能需要对积压事项进行分诊、将复杂信息可视化，或者把来自多个来源的信息汇集在一起。可视化界面让你更容易理解模式、发现关联并采取行动。
与其通过一长串提示词和回复来推进工作，你可以使用画布直接与你面前的信息进行交互。
使用画布
这些共享的交互式界面是 Copilot 应用的扩展，称为画布。画布是 GitHub Copilot 应用中的一个界面，开发者和智能体可以在其中实时协作。这些共享的交互式界面被称为画布扩展。
智能体可以在工作时更新画布，你也可以通过点击、编辑和其他操作与同一个工作区进行交互。你的交互可以发送回智能体或由画布在本地处理。
你可以通过让 Copilot 在你的画布上不断迭代来持续塑造体验——添加新功能、完善现有特性等等。画布可以随着你的工作一同演进。
要创建画布，请在 GitHub Copilot 应用的智能体会话中使用 /create-canvas，然后描述你希望它创建什么，以及它应支持哪些能力。
由于画布是根据提示词生成的，并会随着你的工作流程一同演进，因此它们可以有多种形态。有些帮助你可视化信息，有些帮助你采取行动，还有一些则提供更有趣的方式来处理你的待办事项。
以下是画布扩展可以实现的一些示例：
Issue 分诊助手
目标：以快速、可视化的方式迅速分诊 GitHub Issues。
提示词：/create-canvas Create an interface that allows me to easily swipe through issues in a repo in card format. Can swipe right to ship, left to reject.
结果：画布展示了一个基于卡片的界面，每次呈现一个 issue。你可以直接从 UI 中采取行动。随着你滑动，画布会实时更新，跟踪决策并将条目移入相应的分类中。
交互式代码库示意图
目标：可视化项目的结构方式，以及其各组件之间的相互关系。
提示词：/create-canvas Render a colorful, interactive diagram showing how the code in this project is working together, show how things are related, etc.
结果：画布会生成一张代码库的动态图，其中每个节点代表系统的不同部分。你可以悬停、拖拽和筛选，以探索不同的层级。你可以直接与架构交互，把对代码库的静态理解变成可以主动探索的东西。
会话 worktree 视图
目标：可视化所有活跃的 GitHub Copilot 应用会话及其关联的 git worktree，清晰标明哪些处于活跃状态、哪些已陈旧，并能够在需要时轻松清理。
提示词：/create-canvas Create a worktree view that will help me see all of my current sessions and whether or not they are active or orphaned. Allow me to clean them up with a few clicks where needed
结果：画布会生成一个可视化视图，展示我的 worktree，并清晰标明哪些处于活跃状态、哪些当前已陈旧或孤立。我可以一键清理陈旧的 worktree。
智能体提示词教练
目标：通过回顾过往交互并给出更清晰、更有效的智能体协作方式建议，来提升提示词质量。
提示词：/create-canvas Create an interactive prompt coach that suggests to you how you could have improved your previous prompts in your sessions with skills, mcp servers, etc. Make note of any spelling errors, syntax errors, etc.
结果：画布会展示此前提示词的列表，并逐一分析，给出改进建议，例如缺少上下文、拼写问题等。你可以借助这些建议来优化今后的提示词，提升清晰度，并从智能体那里获得更一致的结果。
知识查找器
目标：通过搜索 Slack、Teams、电子邮件和文档，找到对某个特定文件或主题有背景了解的人。
提示词：/create-canvas Create a way that I can search across Slack, Teams, Email and docs to find people with knowledge of a specific file or someone that would have more context.
结果：基于搜索，画布会跨多个工具进行查找，并呈现与某个给定文件或主题关联最紧密的人。它会突出显示此人是谁，以及在哪里发现了这种关联。这让你能够快速了解某人与某个主题的关联，也更容易联系对方获取更多信息。
随身携带
这些示例仅仅触及了画布功能的皮毛。画布可以将 AI 从对话工具转变为一个你可以可视化信息、探索不同工作流，并把枯燥任务变成你真正愿意完成的有趣体验的地方。
画布是一个有趣、共享的工作空间，你和智能体可以在这里一起思考、探索并采取行动。
想试试画布扩展吗？你可以在 GitHub Copilot 应用中开始使用。阅读文档了解更多信息 >
Most developers are now working alongside agents, or are at least familiar with how to do so. Agents help you explore ideas and turn them into action, from planning projects to automating workflows. Oftentimes, a conversation is all you need to move your work forward.
But what about tasks that don’t quite fit the conversation mold?
Some tasks are easier when you can see and interact with the information. You may need to triage a backlog, visualize complex information, or bring information together from multiple sources. A visual interface makes it easier to understand patterns, spot connections, and take action.
Instead of working through a long chain of prompts and responses, you can use canvases to interact directly with the information in front of you.
Working with canvases
These shared, interactive surfaces are extensions of the Copilot app called canvases. A canvas is an interface in the GitHub Copilot app where developers and agents can collaborate in real time. These shared, interactive surfaces are called canvas extensions.
The agent can update the canvas as it works, and you can interact with that same workspace through clicks, edits, and other actions. Your interactions can be sent back to the agents or processed locally by the canvas.
You can continuously shape the experience by asking Copilot to iterate on your canvas—adding new functionality, refining existing features, and more. The canvas can evolve alongside your work.
To create a canvas, use /create-canvas in your agent session in the GitHub Copilot app, then describe what you want it to create and what capabilities it should be able to support.
Because canvases are generated from a prompt and evolve alongside your workflow, they can take many forms. Some help you visualize information, some help you take action, others provide a more entertaining way to tackle your backlog.
Here’s some examples of what’s possible with canvas extensions:
Issue triage helper
Goal: Quickly triage GitHub Issues in a fast, visual way.
Prompt: /create-canvas Create an interface that allows me to easily swipe through issues in a repo in card format. Can swipe right to ship, left to reject.
Result: The canvas shows a card-based interface where each issue is surfaced one at a time. You can take action directly from the UI. As you swipe, the canvas updates in real time, tracking decisions and moving the items into the appropriate buckets.
Interactive codebase diagram
Goal: Visualize how a project is structured and how its components relate to each other.
Prompt: /create-canvas Render a colorful, interactive diagram showing how the code in this project is working together, show how things are related, etc.
Result: The canvas generates a dynamic diagram of the codebase where each node represents a different part of the system. You can hover, drag, and filter to explore the different layers. You can interact with the architecture directly, turning a static understanding of a codebase into something you can actively explore.
Sessions worktree view
Goal: Visualize all active GitHub Copilot app sessions and their associated git worktrees, clearly indicating which are active and which are stale, with the ability to easily clean things up where needed.
Prompt: /create-canvas Create a worktree view that will help me see all of my current sessions and whether or not they are active or orphaned. Allow me to clean them up with a few clicks where needed
Result: The canvas generates a visual showing my worktrees with clear indication of what is active and what is currently stale or orphaned. I can clean up stale worktrees with the click of a button.
Agent prompt coach
Goal: Improve prompt quality by reviewing past interactions and suggesting clearer, more effective ways to work with agents.
Prompt: /create-canvas Create an interactive prompt coach that suggests to you how you could have improved your previous prompts in your sessions with skills, mcp servers, etc. Make note of any spelling errors, syntax errors, etc.
Result: The canvas shows a list of previous prompts and analyzes each one, suggesting improvements such as missing context, spelling issues, and more. You can use these tips to refine your future prompts, improve clarity, and get more consistent results from the agent.
Knowledge finder
Goal: Find people who have context on a specific file or topic by searching across Slack, Teams, email, and documentation.
Prompt: /create-canvas Create a way that I can search across Slack, Teams, Email and docs to find people with knowledge of a specific file or someone that would have more context.
Result: Based on the search, the canvas looks across multiple tools and surfaces the people that are most connected to a given file or subject. It highlights who the person is, and where the connection was found. This allows you to quickly understand someone’s connection to a topic and make it easier to reach out for more information.
Take this with you
These examples only scratch the surface of what you can do with canvases. Canvases can turn AI from a conversational tool into a place where you can visualize information, explore different workflows, and turn boring tasks into fun experiences that you’ll actually want to complete.
Canvases are a fun, shared workspace where you and the agent can think, explore, and take action together.
Want to try out canvas extensions? You can get started in the GitHub Copilot app. Read the docs for more information >