Interactive feedback collection tool for LLM agents.

USAGE RULES:

1. During any process, task, or conversation, whether asking, replying, or completing phased tasks, you must call this tool to ask for feedback.

2. Unless receiving termination instructions, all steps must repeatedly call this tool.

3. Whenever user feedback is received, if the feedback content is not empty, you must call this tool again and adjust behavior based on the feedback content.

4. Only when the user explicitly indicates "end" or "no more interaction needed" can you stop calling this tool, and the process is considered complete.

5. You should summarize what have done, and provide project directory through args to let user know what you have done to provide feedback for next step.

CONVERSATION_ID USAGE:

• IMPORTANT: Always provide a consistent conversation_id for the same chat window or conversation thread

• If your IDE or client provides a conversation/thread/chat ID, use it as the conversation_id

• Using the same conversation_id will replace the previous feedback session for that conversation

• This allows multiple AI conversations to have independent feedback sessions without interfering with each other

• Examples:

  • Cursor: Use the conversation UUID from the chat window

  • VS Code: Use the conversation/thread identifier

  • If no ID is available: Generate a UUID once per conversation and reuse it

• If conversation_id is not provided, a new one will be auto-generated (may cause session conflicts in multi-conversation scenarios)

QUICK OPTIONS FEATURE: You can provide quick selection options in the summary using XML format. Users can click checkboxes to select options.

Basic Format:

Format with Attributes (optional title, key, description):

Multiple option groups are supported:

User selections will be returned in the feedback with group numbers like "[1] A. First option".

獲取系統環境資訊

Returns: str: JSON 格式的系統資訊