Troubleshoot AI in Visual Studio Code

This article covers diagnostic tools and techniques for troubleshooting AI-related issues in VS Code. Use these tools to identify problems with network connectivity, customization files, and AI responses.

View logs for GitHub Copilot

The log files for the GitHub Copilot extension are stored in the standard log location for Visual Studio Code extensions. Use these logs to diagnose connection issues, extension errors, and unexpected behavior.

To view detailed logs:

Open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)).
Run Developer: Set Log Level and set the value to Trace for the GitHub Copilot and GitHub Copilot Chat extensions.
Run Output: Show Output Channels and select either GitHub Copilot or GitHub Copilot Chat from the list.
In the Output panel, view the logs for the selected extension.

To switch between output channels, select GitHub Copilot or GitHub Copilot Chat from the dropdown menu on the right side of the Output panel.

Collect network diagnostics

If you encounter problems connecting to GitHub Copilot, collect network connectivity diagnostics to identify firewall, proxy, or VPN issues.

Open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)).
Run GitHub Copilot: Collect Diagnostics.
An editor tab opens with diagnostic information you can review and share when reporting issues.

For more information about network configuration, see Network and firewall configuration for Copilot.

Debug chat interactions

VS Code provides different tools to inspect what happens when you send a prompt to the AI.

/troubleshoot slash command:

Ask the AI to analyze the debug logs for the current chat session. Type /troubleshoot followed by your question, such as /troubleshoot how many tokens did I use? or /troubleshoot list all paths you tried to load customizations. Requires github.copilot.chat.agentDebugLog.enabled Open in VS Code Open in VS Code Insiders to be enabled.
Agent Debug Log panel (Preview):

Shows a chronological event log of agent interactions during a chat session, including tool call sequences, LLM requests, token usage, prompt file discovery, and errors. This is the primary tool for understanding and debugging chat interactions.

To open the Agent Debug Log panel:
1. Select the gear icon in the Chat view.
2. Select Show Agent Debug Logs.
From the Agent Debug Log panel, you can attach a snapshot of the agent debug events to a chat conversation to ask the AI questions about the session and troubleshoot a specific interaction.

Learn more about the Agent Debug Log panel.
Chat Debug view:

Shows the raw details of each LLM request and response, including the full system prompt, user prompt, context, and tool invocation payloads. Use this view to inspect the exact data sent to and received from the language model for each interaction.

To open the Chat Debug view:
1. Select the overflow menu (...) in the Chat view.
2. Select Show Chat Debug View.

Learn more about the Chat Debug view.

Troubleshoot MCP servers

MCP servers extend chat capabilities by connecting to external services. If an MCP server isn't working correctly, you can view its logs and restart it.

To troubleshoot MCP servers:

Open the Command Palette and run MCP: List Servers.
Select a server to view its status and available actions.
Select Show Output to view the server's logs.
Select Restart Server to restart a misbehaving server.

Learn more about configuring and debugging MCP servers.

Provide feedback

If you encounter issues that you can't resolve, report them to help improve GitHub Copilot:

Ghost text suggestions: Hover over a ghost text suggestion in the editor and select Send Copilot Completion Feedback.
Next edit suggestions: Select the Feedback action in the next edit suggestions menu in the editor gutter.
General issues: Open Help > Report Issue, select VS Code Extension, and choose GitHub Copilot Chat.

When reporting issues, include relevant information from the Copilot logs to help diagnose the problem.

Related resources

3/18/2026