Visual Studio Code 1.118

Visual Studio Code 1.118

Follow us on LinkedIn, X, Bluesky Release date: April 29, 2026 Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the 1.118 release of Visual Studio Code. This release expands where you can work with Copilot agents and makes them more efficient. Here are the highlights for this release:

• Remote control: Track and control your ongoing Copilot CLI sessions remotely from GitHub.com or mobile.
• Codebase search: Find the code you need with semantic search in any workspace and text search across GitHub repos and orgs.
• Dedicated context for skills: Isolate skill execution to keep your main chat focused and answers sharper.
• Chat session insights: Turn your chat history into standup reports, tips, and answers about past work.
• Enterprise control: Restrict AI feature access to organizations your admin trusts.
• Improved token efficiency: Get more out of every request with lower token usage. Happy Coding! VS Code is rolling out gradually to all users. Use Check for Updates in VS Code to get the latest version immediately. To try new features as soon as possible, download the nightly Insiders build, which includes the latest updates as soon as they are available.

Agent experience

Visual Studio Code Agents (Insiders)

Note: The Visual Studio Code Agents app is currently in preview and only available when installing VS Code Insiders. The Visual Studio Code Agents app is a companion app that ships alongside VS Code Insiders. It provides a focused, agent-native environment where you can run parallel sessions across repos and iterate on multi-step coding tasks. We first introduced the Agents app in 1.115 and continue to refine it based on user feedback. In this release, you can discover the Agents app directly from the VS Code Insiders title bar, making it easy to jump into an agent-powered workflow. We also published dedicated Agents documentation to help you get started. Recent feature highlights include:

• Shared state across VS Code and Agents: The Agents app shares more state with VS Code Insiders for a smoother transition between the two. This includes authentication (on Windows), AI customizations, workspace trust, recent folders, and keyboard shortcuts.
• Claude agent: The Claude Agent is available in the Agents app, so that you can use it alongside other agents like Copilot CLI or Copilot Cloud for your coding tasks.
• Web client: Access the Agents experience from the browser at insiders.vscode.dev/agents, bringing the agent-native workflow to any machine where you have a Dev Tunnel running (via code-insiders tunnel). To get started, download VS Code Insiders and run code-insiders tunnel to set up a Dev Tunnel. You can then connect to it from the web.
• Background browsers: The integrated browser persists across sessions, so it no longer refreshes when you return to a session. This makes context switching smoother when using the integrated browser to preview changes while the agent works.
• Layout controls for changes: When the agent makes changes, you can open the diff view side-by-side with the Chat view or open it in a modal window to focus on the changes. Use the layout controls in the diff view toolbar to toggle between different display modes.
• Dynamic title bar entry points: Switch between VS Code Insiders and the Agents app with a single click. Select Open in Agents from the VS Code Insiders title bar to jump into the Agents app, or select Open in VS Code from the Agents title bar to return to the Insiders editor. Your feedback helps us shape the Agents experience - please continue sharing it with us by filing issues on GitHub. You can also explore existing issues to see what others have reported and provide your feedback on specific topics.

Remote control for Copilot CLI sessions (Experimental)

Setting: github.copilot.chat.cli.remote.enabled Previously, to engage with a Copilot CLI session, you had to be at the machine where you started it. If the agent paused for an approval or hit a question while you were away from your desk, the work stalled until you returned. With remote control, you can monitor and steer your ongoing Copilot CLI sessions from anywhere, giving you more flexibility to keep work moving without being tied to your machine. Remote control for Copilot CLI lets you check progress, respond to approvals, and steer work from another device (using GitHub.com or the GitHub mobile app), while your Copilot CLI session keeps running in the background. To try remote control:

• Enable the github.copilot.chat.cli.remote.enabled setting.
• Enter /remote on in a Copilot CLI chat to get started. You can always run /remote to view remote control status, or /remote off to disable remote control.

Synced session titles for Copilot CLI

The chat session title is used across different chat surfaces like the chat sessions list, the chat editor tab and header, and the Copilot CLI terminal interface to provide a consistent identifier for the session. Depending on where you renamed a Copilot CLI session, other chat surfaces could still show the old title. VS Code adopts the Copilot SDK session title APIs as the source of truth and routes the sessions list and chat editor header through a single title resolver to keep the displayed title consistent across surfaces. The chat sessions list, the chat editor tab and header, and copilot --resume in the terminal now all stay in sync when you rename a session, regardless of where the rename originated. Renames performed in the terminal from Copilot CLI are also picked up by VS Code the next time the session metadata is read.

Copilot added as a Git co-author by default

VS Code now enables Git AI co-authoring by default for chat and agent workflows. When Copilot makes changes to your files, Copilot is automatically added as a co-author on that commit. You can change the default behavior using git.addAICoAuthor .

Codebase search and context

Semantic indexing of non-GitHub repositories rolled out to all users

When you ask Copilot a question like "where do we handle user authentication?", the agent has to translate your fuzzy intent into the exact files and symbols that matter. Plain text search only matches the literal words you typed, so it often misses the relevant code when your codebase uses different terminology. Semantic indexing lets agents search by meaning, surfacing files that use related terms like login, signIn, verifyCredentials, or OAuth token exchange, even if the word "authentication" never appears in the code. This gives the agent better grounding for answers and edits. Semantic indexing is now available in all workspaces. Previously, this capability was limited to workspaces that use GitHub or ADO repositories. The semantic index is built and maintained automatically. Workspaces that use a GitHub or ADO repository can typically use semantic search instantly, while other workspaces might require a few minutes to build up the initial index. You can also use the Build Codebase semantic index command to explicitly build the index for the current workspace. Semantic search is one of the many tools Copilot uses to understand your workspace when answering questions and generating edits. Copilot will pick the best tools for the job, so you generally do not have to micromanage how it searches. Check out the How Copilot understands your workspace docs for more details on semantic search and the other tools that Copilot uses.

GitHub text search across repos or orgs

When the agent needs to look up an exact string, API name, or error message in code outside your current workspace, semantic search isn't always the right fit. You want a precise match across a known repository or your entire organization, not a fuzzy one. To support this, Copilot now includes a built-in githubTextSearch agent tool that does a grep-style search through the code of a GitHub repository or an entire GitHub organization. This complements the existing githubRepo tool, which does semantic searches within a GitHub repo. Together, these tools give the agent a richer way to learn from codebases outside the one you are currently working on. For more advanced GitHub features such as searching and managing issues or pull requests, consider using the GitHub MCP server.

Dedicated context for skills (Experimental)

Setting: github.copilot.chat.skillTool.enabled When you use a skill that performs multi-step tool calls or pulls in large reference material, that auxiliary content can crowd your main chat context and degrade the quality of follow-up responses. You can now run a skill in a dedicated subagent context that isolates its execution from the main conversation, so your primary context stays focused and skill responses remain higher quality. To run a skill in a dedicated subagent context, set the context attribute in the SKILL.md frontmatter: --- name: my-skill description: My skill description context: fork --- This feature is experimental and requires the github.copilot.chat.skillTool.enabled setting to be enabled.

Workspace .mcp.json files and server deduplication

We've added support for workspace-level .mcp.json files to declare MCP servers, aligning with other tools such as the Copilot CLI. Additionally, we've introduced behavior to deduplicate MCP servers that share the same name. By default, only the most-specific MCP server will be enabled, and enabling a server will disable other servers by the same name. You can control which MCP servers are enabled by searching @mcp @installed in the extensions view, or via the Chat: Open Customizations window.

Improving token efficiency

On April 27, GitHub announced that Copilot is moving to usage-based billing on June 1, 2026. To help you get the most value out of your plan, we have been working on several initiatives to improve token efficiency without hindering the quality of the agent. Most of the improvements described below are already in place. Where an opt-in setting is available, it is noted in the relevant section.

Prompt caching efficiency

Over the past several iterations, we have improved cache reuse across system prompts, tools, conversation history, and summarization, without changing how the agent behaves. In practice, this means repeated context is billed at a much lower token rate (for example, about 10x lower for Anthropic models), which helps reduce cost in longer, multi-turn agent workflows. Strategic cache breakpoint placement. We audited where cache breakpoints are set so they are used efficiently and placed at stable boundaries: end of system prompt, end of tools, end of the most recent tool turn, and conversation turn boundaries. As a result, once an agent session is underway, more than 93% of each request is reused from cache instead of being charged as new input. A cache-stable system prompt and tools list. A cached prefix is only as good as the bytes that precede it. We reviewed the system prompt and tool registration paths to remove sources of byte drift across requests. For example, the new chat.experimental.symbolTools.cacheStable registers vscode_renameSymbol and vscode_listCodeUsages with a static description instead of one that changes based on which languages are loaded. That way, when a language extension activates partway through a session, it no longer changes the request and resets the cache. We also re-ordered the tools list so deferred and non-deferred tools are grouped predictably, keeping the tools-array bytes identical across turns. Cache-friendly background compaction. As a session gets long, we summarize older turns in the background so the agent can keep working without running out of context. The model can still look up tool results and details from earlier turns when it needs them. These background summaries now reuse the same cached context as the main agent, making long, multi-turn sessions noticeably more efficient. …