Making Copilot Chat an expert in your workspace

Referencing @workspace in Copilot Chat lets you ask questions about your entire codebase. Based on the question, Copilot intelligently retrieves relevant files and symbols, which it then references in its answer as links and code examples. Grounded in @workspace references, Copilot Chat becomes a domain expert for tasks like:

• Finding existing code in your codebase:
  • "@workspace where is database connecting string configured?" - Explains where and how the database connection is configured
  • "@workspace how can I validate a date?" - Finds existing date validation helpers in the codebase
  • "@workspace where are tests defined?" - Provides the location of test suites, cases, and related references and configurations
• Making plans for complex code edits:
  • "@workspace how can I add a rich tooltip to a button?" - Provides a plan for using the existing tooltip component with button elements
  • "@workspace add date validation to #selection" - Plans how to apply the existing date validation to the selected code
  • "@workspace add a new API route for the forgot password form" - Outlines where to add the new route and how to connect it to the existing code
• Explaining higher-level concepts in a codebase:
  • "@workspace how is authentication implemented?" - Overview of the authentication flow and references to the relevant code
  • "@workspace which API routes depend on this service?" - Lists the routes that use the service in the selected code
  • "How do I build this #codebase?" - List the steps to build the project based on documentation, scripts, and configurations

What sources does @workspace use for context?

To answer your question, @workspace searches through the same sources a developer would use when navigating a codebase in VS Code:

• All files in the workspace, except for files that are ignored by a .gitignore file
• Directory structure with nested folder and file names
• GitHub's code search index, if the workspace is a GitHub repository and indexed by code search
• Symbols and definitions in the workspace
• Currently selected text or visible text in the active editor

How does @workspace find the most relevant context

Your full VS Code workspace can be too large to pass entirely to GitHub Copilot for responding to your chat prompt. Instead, @workspace extracts the most relevant information from the different context sources to ground Copilot's answer.

First, @workspace determines which information is needed to answer your question, also including the conversation history, workspace structure, and currently selected code.

Next, it collects the context using different approaches, such as finding relevant code snippets by searching locally or by using GitHub's code search, and using VS Code's language IntelliSense to add details like function signatures, parameters, and more.

Finally, this context is used by GitHub Copilot to answer your question. If the context is too large, only the most relevant parts of the context are used. The response is marked up with references to files, file ranges, and symbols. This enables you to link directly from the chat response to the corresponding information in your codebase. The code snippets that were provided to Copilot are listed as references in the response.

Context for @workspace slash commands

@workspace provides several slash commands as shorthand for commonly used tasks, saving you time and typing effort. Each command defines its own optimized context, often eliminating the need for additional prompting or chat variables. Here are the available slash commands and their contexts:

You can explicitly expand the context by using chat variables, such as #editor, #selection, or #file in your chat prompt. For example, to fix an error in the current file based on a pattern from another file, use this chat prompt: @workspace /fix linting error in the style of #file:form.ts.

Tips for using @workspace

The way you phrase your question can significantly influence the quality of the references @workspace provides and the accuracy of the response. To optimize results, consider the following tips:

• Be specific and detailed in your question, avoiding vague or ambiguous terms like "what does this do" (where "this" could be interpreted as the last answer, current file, or whole project, etc.).
• Incorporate terms and concepts in your prompt that are likely to appear in your code or its documentation.
• Review the used references in the response to ensure that the files are relevant. Iterate on your question if necessary.
• Explicitly include relevant context by selecting code or mentioning chat variables such as #editor, #selection, or #file.
• Responses can draw from multiple references, such as "find exceptions without a catch block" or "provide examples of how handleError is called". However, don't anticipate a comprehensive code analysis across your codebase, such as "how many times is this function invoked?" or "rectify all bugs in this project".
• Avoid assuming information beyond the code (for now), such as "who contributed to this file?" or "summarize review comments for this folder".

Related resources

• Get started with the Copilot Chat tutorial
• Use the Chat Participant API to build a chat extension