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