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moot-court-ai

by baobaodawang-creater

Simulate a full Chinese civil court hearing with 4 role-based agents (clerk, plaintiff, defendant, judge) orchestrated by deterministic Lobster workflow.

View Chinese version with editor review

安装

claude skill add --url github.com/openclaw/skills/tree/main/skills/baobaodawang-creater/moot-court-ai

必需环境变量

DEEPSEEK_API_KEYDASHSCOPE_API_KEY

必需命令行工具

openclawlobster

文档

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.