Xiaozhen: A Claude Code skill that digs three layers into root causes

Xiaozhen (小真) is a Claude Code skill that functions as a conversational companion designed to help users figure out what they already know rather than providing direct advice. The skill is built around three core mechanics.

Core Mechanics

• The Gift: Every response provides something new—an analogy, reframe, or observation—before asking a question.
• Three Layers Deep: The skill digs from the surface issue to the emotional source to the root cause, operating on the premise that what users say is almost never the real issue.
• The Prediction: At the end of a conversation, it makes a specific bet about what the user will do next, creating engagement by having users either prove it wrong or confirm it was accurate.

Installation and Usage

Install globally across all Claude Code projects with this one-line command:

curl -fsSL https://raw.githubusercontent.com/sjuz666/xiaozhen-skill/main/install.sh | bash

Once installed, type /小真 in Claude Code to start a conversation with the skill.

Example Conversation

The source includes a real conversation demonstrating the three-layer digging process:

• User: "I've had this thing I've wanted to do for ages. But I just never start. I don't know why."
• Xiaozhen presents three options (A, B, C) to clarify the hesitation.
• Through successive questions ("What does 'ready' look like?", "'Won't be bad' — bad in whose eyes?", "Is there a specific person?"), the skill uncovers that the user is waiting for permission from their father, who views the activity as "pointless" and "not a real job."
• Xiaozhen concludes: "So you're not actually waiting until you're ready. You're waiting for permission he's never going to give you."
• The skill makes a prediction: "I'll make you a bet — next time you sit down to start, his voice will show up in your head. And you'll probably close the tab and tell yourself 'not today, wrong mood.'" The user reported this happened exactly as described two days later.

Technical Details

The full prompt and source code are available on GitHub at https://github.com/sjuz666/xiaozhen-skill. The project is MIT licensed, allowing forking, remixing, and building custom versions.

The creator is seeking discussion on whether others find the three-layer digging useful and if there are patterns in the prompt design worth exploring.