moot-court-ai

name	moot-court-ai
description	Simulate a full Chinese civil court hearing with 4 role-based agents (clerk, plaintiff, defendant, judge) orchestrated by deterministic Lobster workflow.
version	1.0.0
metadata	{"openclaw":{"requires":{"env":"[Truncated]","bins":"[Truncated]"},"primaryEnv":"DEEPSEEK_API_KEY","emoji":"⚖️","homepage":"https://github.com/baobaodawang-creater/moot-court-ai"}}

Moot Court AI

Moot Court AI is an OpenClaw skill that runs a 4-agent Chinese civil court simulation with strict workflow control.

Agent system

• clerk (书记员): announces opening, checks identity, controls stage transitions.
• plaintiff (原告代理律师): argues for plaintiff, presents claim and evidence.
• defendant (被告代理律师): performs three-validity challenges and defense.
• judge (审判长): stays neutral, summarizes issues, applies legal syllogism, and renders judgment.

Model stack

• DeepSeek: deepseek-chat, deepseek-reasoner
• Qwen: qwen-max (DashScope compatible endpoint)

Workflow principle

• Deterministic orchestration with Lobster.
• Agent communication follows fixed hearing stages.
• Process follows Chinese civil procedure order (庭前准备 -> 诉辩交换 -> 举证质证 -> 法庭辩论 -> 最后陈述 -> 宣判).

Installation requirements

You must configure both API keys before running:

• DEEPSEEK_API_KEY
• DASHSCOPE_API_KEY

Recommended usage

1. Prepare case files (case-brief.md, complaint.md, defense.md, evidence folders).
2. Initialize materials into agent workspaces.
3. Run moot-court.lobster through OpenClaw/Lobster.
4. Export judgment and hearing log for review.