Copilot Chat: IDEA vs VSCode Context | Generated by AI

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GitHub Copilot Chat is an AI-powered assistant integrated into both JetBrains IDEA and Visual Studio Code (VS Code), designed to help developers with coding tasks through natural language interactions, code suggestions, and context-aware assistance. While the core functionality of Copilot Chat is similar across both IDEs, there are differences in implementation, context handling, and feature availability due to the distinct architectures and ecosystems of JetBrains IDEA and VS Code. Below is a comprehensive explanation of the differences, with a focus on how recent files are handled as context and other key distinctions.

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1. Context Awareness and Handling of Recent Files

One of the primary differences between Copilot Chat in JetBrains IDEA and VS Code lies in how they handle context, particularly the inclusion of recent files.

JetBrains IDEA: Context with Recent Files

• Behavior: In JetBrains IDEA, Copilot Chat tends to leverage the IDE’s robust project indexing and context-awareness capabilities. JetBrains IDEs are known for their deep understanding of project structure, including file relationships, dependencies, and recently opened files. Copilot Chat in IDEA uses this to include recent files as part of the context for generating responses, even if they are not explicitly referenced by the user.
• Mechanism: When you interact with Copilot Chat in JetBrains IDEA, it draws context from:
  • The currently open file in the editor.
  • Recently opened or active files in the project, which are part of the IDE’s internal index.
  • The project’s codebase structure, especially when using features like the @project context (introduced in early 2025), which allows Copilot to analyze the entire codebase for relevant files and symbols.
• Advantages:
  • Seamless Integration with Project Context: JetBrains’ indexing makes it easier for Copilot to provide suggestions that align with the project’s structure, such as referencing classes, methods, or dependencies in recently edited files.
  • Recent Files as Implicit Context: If you’ve recently worked on a file, Copilot may include it in its context without requiring manual specification, which is useful for maintaining continuity in a coding session.
• Limitations:
  • The reliance on recent files can sometimes lead to less precise context if the IDE includes irrelevant files. For example, if you’ve opened many files recently, Copilot might pull in outdated or unrelated context.
  • Until recently (e.g., the @project feature in February 2025), JetBrains lacked an explicit way to include the entire codebase as context, unlike VS Code.

VS Code: Context with Explicit and Flexible Options

• Behavior: In VS Code, Copilot Chat has more explicit and customizable context management, with features like #codebase, #file, and other chat variables that allow users to define the scope of context. While it can use recently opened files, it does not automatically prioritize them as heavily as JetBrains IDEA unless explicitly instructed.
• Mechanism: VS Code’s Copilot Chat gathers context from:
  • The active file in the editor.
  • Files explicitly referenced using #file or #codebase in the chat prompt. For example, #codebase searches the entire workspace, while #file:<filename> targets a specific file.
  • Workspace indexing, which can include a local or remote (GitHub-hosted) index of the codebase, especially when the github.copilot.chat.codesearch.enabled setting is enabled.
  • Additional context sources like terminal output, test results, or web content via #fetch or #githubRepo.
• Advantages:
  • Granular Control: Users can precisely specify which files or parts of the codebase to include, reducing noise from irrelevant files.
  • Whole-Codebase Search: The @workspace and #codebase features allow Copilot to search across all indexable files in the workspace, which is particularly powerful for large projects.
  • Dynamic Context Addition: Features like drag-and-drop images, terminal output, or web references provide flexibility for adding diverse context types.
• Limitations:
  • VS Code does not automatically prioritize recently opened files as heavily as JetBrains IDEA, which may require users to manually specify context more often.
  • For very large codebases, the context might be limited to the most relevant files due to indexing constraints (e.g., local indexes are capped at 2500 files).

Key Difference in Recent Files Context

• JetBrains IDEA: Automatically includes recently opened files as part of its context due to the IDE’s project indexing, making it feel more “implicit” and seamless for users working within a single project. However, this can sometimes include irrelevant files if the user has opened many files recently.
• VS Code: Requires more explicit context specification (e.g., #file or #codebase) but offers greater control and flexibility. Recent files are not automatically prioritized unless they are open in the editor or explicitly referenced.

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2. Feature Availability and Integration

Both IDEs support Copilot Chat, but the depth of integration and feature rollout differ due to the development priorities of GitHub (owned by Microsoft, which also maintains VS Code) and the distinct ecosystems of JetBrains and VS Code.

JetBrains IDEA: Tighter IDE Integration but Slower Feature Rollout

• Integration: Copilot Chat is deeply integrated into JetBrains IDEA through the GitHub Copilot plugin, leveraging the IDE’s robust features like IntelliSense, project indexing, and refactoring tools. Inline Chat, introduced in September 2024, allows users to interact with Copilot directly in the code editor (Shift+Ctrl+I on Mac, Shift+Ctrl+G on Windows).
• Features:
  • Inline Chat: Supports focused interactions for refactoring, testing, and code improvement within the active file.
  • @project Context: As of February 2025, Copilot in JetBrains supports querying the entire codebase with @project, providing detailed answers with references to relevant files and symbols.
  • Commit Message Generation: Copilot can generate commit messages based on code changes, enhancing workflow efficiency.
• Limitations:
  • Features often lag behind VS Code. For example, multi-model support (e.g., Claude, Gemini) and multi-file editing in agent mode were introduced in VS Code before JetBrains.
  • Some advanced features, like attaching images to prompts or agent mode for autonomous multi-file edits, are not yet fully supported in JetBrains as of the latest updates.
• Performance: JetBrains’ heavier IDE environment may result in slightly slower Copilot responses compared to VS Code, especially in large projects, due to the overhead of its indexing and analysis engine.

VS Code: Faster Feature Rollout and Broader Functionality

• Integration: As a Microsoft product, VS Code benefits from tighter integration with GitHub Copilot and faster feature rollouts. Copilot Chat is seamlessly embedded in the editor, with access through the Chat view, inline chat (⌘I on Mac, Ctrl+I on Windows), or smart actions via the context menu.
• Features:
  • Multiple Chat Modes: Supports ask mode (general questions), edit mode (multi-file edits with user control), and agent mode (autonomous multi-file edits with terminal commands).
  • Custom Instructions and Prompt Files: Users can define coding practices in .github/copilot-instructions.md or .prompt.md files to customize responses across both VS Code and Visual Studio.
  • Image Attachments: Since Visual Studio 17.14 Preview 1, users can attach images to prompts for additional context, a feature not yet available in JetBrains.
  • Multi-Model Support: VS Code supports multiple language models (e.g., GPT-4o, Claude, Gemini), allowing users to switch models for different tasks.
  • Workspace Indexing: The @workspace feature and #codebase searches provide comprehensive codebase context, enhanced by remote indexing for GitHub-hosted repositories.
• Advantages:
  • Rapid Feature Updates: VS Code often receives Copilot features first, such as agent mode and multi-model support.
  • Lightweight and Flexible: VS Code’s lightweight nature makes Copilot responses faster in most cases, and its extension ecosystem allows for additional AI tools or customizations.
• Limitations:
  • Less robust project indexing compared to JetBrains, which may require more manual context specification.
  • The extension-based architecture can feel less cohesive than JetBrains’ all-in-one IDE experience for some users.

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3. User Experience and Workflow

The user experience of Copilot Chat in each IDE reflects the design philosophy of the respective platforms.

JetBrains IDEA: Streamlined for Heavy IDE Users

• Workflow: Copilot Chat integrates into JetBrains’ comprehensive IDE environment, which is tailored for developers working on large, complex projects. The inline chat and side panel chat provide focused and broad interaction modes, respectively.
• Contextual Awareness: The IDE’s deep understanding of project structure and recent files makes Copilot feel more “aware” of the project without requiring extensive manual context specification.
• Use Case: Ideal for developers who rely on JetBrains’ advanced refactoring, debugging, and testing tools and prefer a unified IDE experience. Copilot enhances this by providing context-aware suggestions within the same workflow.
• Learning Curve: JetBrains’ feature-rich environment can be overwhelming for new users, but Copilot’s integration is relatively intuitive once the plugin is set up.

VS Code: Flexible for Diverse Workflows

• Workflow: Copilot Chat in VS Code is designed for flexibility, catering to a wide range of developers from lightweight scripting to large projects. The Chat view, inline chat, and smart actions provide multiple entry points for interaction.
• Contextual Awareness: While powerful, VS Code’s context management requires more user input to achieve the same level of project awareness as JetBrains. However, features like #codebase and custom instructions make it highly customizable.
• Use Case: Suited for developers who prefer a lightweight, customizable editor and need to work across diverse projects or languages. The ability to integrate web content, images, and multiple models enhances its versatility.
• Learning Curve: VS Code’s simpler interface makes Copilot Chat more accessible to beginners, but mastering context management (e.g., #-mentions) requires some familiarity.

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4. Specific Differences in Context of Latest Files

• JetBrains IDEA:
  • Automatically includes recently opened files in the context, leveraging the IDE’s project indexing. This is particularly useful for developers who frequently switch between related files in a project.
  • The @project feature (introduced February 2025) allows querying the entire codebase, but recent files are still prioritized implicitly due to JetBrains’ indexing.
  • Example: If you’ve recently edited a utils.py file and ask Copilot to generate a function, it may automatically consider code from utils.py without needing to specify it.
• VS Code:
  • Relies on explicit context specification (e.g., #file:utils.py or #codebase) rather than automatically prioritizing recent files. However, open files in the editor are included in the context by default.
  • Example: To include utils.py in the context, you must explicitly reference it or have it open in the editor, or use #codebase to search the entire workspace.
• Practical Impact:
  • JetBrains: Better for workflows where recent files are likely relevant, reducing the need for manual context specification.
  • VS Code: Better for workflows where precise control over context is preferred, especially in large projects where recent files might not always be relevant.

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5. Other Notable Differences

• Multi-Model Support:
  • VS Code: Supports multiple language models (e.g., GPT-4o, Claude, Gemini), allowing users to switch based on task requirements.
  • JetBrains IDEA: Lags in multi-model support, with Copilot primarily using GitHub’s default models. JetBrains’ own AI Assistant may offer alternative models, but integration with Copilot is limited.
• Agent Mode:
  • VS Code: Supports agent mode, which autonomously edits multiple files and runs terminal commands to complete tasks.
  • JetBrains IDEA: Agent mode is not yet available, limiting Copilot to user-controlled edits or single-file interactions.
• Custom Instructions:
  • VS Code: Supports custom instructions via .github/copilot-instructions.md and prompt files, allowing users to define coding practices and project requirements.
  • JetBrains IDEA: Supports similar custom instructions but is less flexible, as the focus is on leveraging JetBrains’ built-in indexing rather than external configuration files.
• Performance:
  • VS Code: Generally faster due to its lightweight architecture, especially for smaller projects.
  • JetBrains IDEA: May experience slight delays in large projects due to the IDE’s resource-intensive indexing, but this enables richer context awareness.

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6. Summary Table

Feature/Aspect	JetBrains IDEA	VS Code
Context of Recent Files	Automatically includes recently opened files via IDE indexing.	Requires explicit context specification (e.g., #file, #codebase).
Whole-Codebase Context	@project feature (Feb 2025) for querying entire codebase.	@workspace and #codebase for searching entire workspace.
Inline Chat	Supported (Shift+Ctrl+I/G) for focused interactions.	Supported (⌘I/Ctrl+I) with broader smart actions.
Multi-Model Support	Limited; primarily uses GitHub’s default models.	Supports GPT-4o, Claude, Gemini, and more.
Agent Mode	Not available.	Available for autonomous multi-file edits and terminal commands.
Custom Instructions	Supported but less flexible; relies on IDE indexing.	Highly customizable via .github/copilot-instructions.md and prompt files.
Feature Rollout	Slower; features lag behind VS Code.	Faster; often receives new features first.
Performance	Slower in large projects due to heavy indexing.	Faster due to lightweight architecture.
Use Case	Best for complex projects with deep IDE integration.	Best for flexible, lightweight workflows across diverse projects.

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7. Recommendations

• Choose JetBrains IDEA with Copilot Chat if:
  • You work on large, complex projects where JetBrains’ project indexing and automatic inclusion of recent files streamline your workflow.
  • You prefer a cohesive, feature-rich IDE with deep language support and don’t mind slower feature rollouts.
  • You value implicit context awareness for recent files and project structure.
• Choose VS Code with Copilot Chat if:
  • You need precise control over context (e.g., specific files, web content, or codebase searches).
  • You want access to the latest Copilot features, such as agent mode, multi-model support, or image attachments.
  • You prefer a lightweight, customizable editor for diverse projects or quick prototyping.

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Conclusion

The key difference in Copilot Chat between JetBrains IDEA and VS Code lies in context handling: JetBrains IDEA automatically includes recently opened files due to its robust project indexing, making it more seamless for project-focused workflows, while VS Code offers explicit and flexible context management, ideal for users who prefer granular control. Additionally, VS Code tends to receive new features faster and supports more advanced functionalities like agent mode and multi-model selection. Your choice depends on whether you prioritize JetBrains’ deep IDE integration or VS Code’s flexibility and rapid updates. For the latest information on Copilot features, check the GitHub Copilot documentation or JetBrains plugin updates.

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