Editor is Qoder’s core AI workspace in the IDE: you get real-time code predictions and completions through Next Edit Suggestion while coding, and can use Ask or Agent in the chat panel for questions, edits, and multi-step work.Documentation Index
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Start a new chat
Open the chat panel
After signing in to Qoder, click the toggle AI sidebar button in the top right corner to open the chat panel. You can also use the shortcut:| Action | macOS | Windows |
|---|---|---|
| Open / close chat panel | ⌘ L | Ctrl L |
View chat history
Click the history icon in the top right corner of the chat panel to view all chat history.Choose a mode
- Ask: Q&A mode that answers programming questions, provides solutions, and offers suggestions based on context, without modifying code.
- Agent: Autonomous coding mode featuring self-decision making, environment awareness, and tool usage. Leveraging tools like project search, planning, file editing, and terminal operations, it completes coding tasks end-to-end. Supports MCP tool configuration to deeply integrate with your development workflow.
Input requirements
After selecting a mode, describe your request in the input box. The following tips can help you achieve better results:- Structured requests: Clearly state what you want Qoder to do, outlining the goals and steps of your coding task.
- Provide context: Attach files, images, code changes, and other relevant information to help Qoder understand the background and generate more accurate solutions.
- Clear expectations: Specify preferences or guidelines, such as programming language, coding standards, output format, or change objectives. For example: “When generating code changes, please add comments for each method.”
- Iterative feedback: Provide feedback on code suggestions or answers. For complex tasks, break down the requirements and iterate step-by-step, collaborating with Qoder to complete them.
Next Edit Suggestion
In addition to interacting with AI in the Chat panel, Qoder provides the Next Edit Suggestion feature seamlessly integrated into the code editor. Based on your current cursor position, context, and recent changes, it automatically predicts and generates the code you are likely to write next. Simply pressTab to quickly accept the suggestion, making your coding process much smoother.
Separate chat windows
Separate chat windows allow you to split ongoing conversations into individual windows. When initiating multiple Agent tasks simultaneously, you can view the execution progress and results of each task in parallel, freeing you from switching back and forth between tabs.How to use
At the top of the Chat panel, right-click the conversation tab you want to separate, and select Move into New Window from the right-click menu. The conversation will open in an independent window. The separated window is completely independent of the main window. You can freely adjust its size and position, distributing them flexibly across multiple screens.Use cases
- Parallel multi-task monitoring: When running multiple Agent tasks simultaneously, allocate different sessions to separate windows to monitor the execution status of each task in real time.
- Split-screen comparison: When you need to compare the output of two sessions, place them side-by-side in left and right windows for easy viewing.
Recommendation cards
After the agent completes a task turn and replies, a set of recommendation cards will automatically appear at the end of the message. Based on current code changes, project status, and conversation context, these cards predict your most likely next step—click to populate it directly into the input box, ready to be sent or further edited. After the agent finishes execution, it will generate new recommendation cards based on the latest context.Recommendation types
- Review Code Changes: Triggered after the agent completes code generation or modification, allowing you to review whether the new code meets project standards and check for potential defects.
- Run Feature Test: Triggered when changes to frontend files (.tsx, .jsx, .vue, .html, .css) are detected, enabling you to verify page rendering and interaction effects in the browser.
- AI Suggestion: Generated autonomously by the agent based on the current conversation context.
- Recommendation cards are inferred from context and may not exactly match your actual intent.
- Recommendation cards are only clickable on the latest agent reply; they will disappear from the previous turn once a new message is sent.
- Tasks triggered by clicking recommendation cards follow the billing rules of the model selected for the current session.