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Moot Court AI
by
baobaodawang-creater
· GitHub ↗
· v1.0.0
· MIT-0
239
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0
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0
Active Installs
1
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Install in OpenClaw
/install 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.
Usage Guidance
This skill is plausible but incomplete. Before installing or providing API keys: (1) confirm the referenced 'moot-court.lobster' workflow exists and inspect it (the skill bundle does not include it); (2) verify the GitHub homepage and author to ensure the workflow is legitimate; (3) understand what local files the agents will read — do not place secrets in case files; (4) limit the API keys’ permissions or use dedicated/test keys for DeepSeek/DashScope; (5) run the skill in an isolated environment if you must test it. If the maintainer can supply the missing lobster workflow and a clear runbook, re-evaluate; otherwise treat this package as incomplete and proceed cautiously.
Capability Analysis
Type: OpenClaw Skill
Name: moot-court-ai
Version: 1.0.0
The moot-court-ai skill bundle is a simulation tool for Chinese civil court proceedings using a multi-agent workflow. The provided files (SKILL.md and _meta.json) describe a legitimate orchestration of agents (clerk, judge, etc.) using the Lobster workflow engine and standard LLM providers (DeepSeek, Qwen). No malicious code, data exfiltration, or suspicious prompt-injection instructions were identified.
Capability Assessment
Purpose & Capability
Name/description describe a Lobster-orchestrated 4-agent simulation and require openclaw + lobster binaries and two model API keys, which is coherent; however the SKILL.md references running a 'moot-court.lobster' workflow and deterministic Lobster orchestration while no workflow file or runtime artifacts are included in the skill bundle. That omission makes the skill incomplete and undermines the claim it will provide the orchestration.
Instruction Scope
Instructions expect the user to prepare case files and 'initialize materials into agent workspaces', then run the lobster workflow. This reasonably implies the agent will read user-supplied files (case briefs, complaints, evidence). The instructions are otherwise high-level and do not ask for unrelated system data, but they are vague about where the lobster file comes from and how agent workspaces are populated.
Install Mechanism
There is no install script (instruction-only), so nothing is written to disk by the skill itself. This is low-risk from an install perspective, but it increases reliance on external files and binaries being present and correct.
Credentials
The two required env vars (DEEPSEEK_API_KEY, DASHSCOPE_API_KEY) match the declared model stack (DeepSeek and a DashScope-compatible Qwen endpoint). Requesting two model keys is proportionate to a multi-model orchestration; no unrelated credentials are requested.
Persistence & Privilege
The skill does not request always: true and declares no config paths. Autonomous invocation is allowed (default) but not combined with elevated persistence or cross-skill config changes.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install moot-court-ai - After installation, invoke the skill by name or use
/moot-court-ai - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: 4-agent Chinese civil court simulation
Metadata
Frequently Asked Questions
What is Moot Court AI?
Simulate a full Chinese civil court hearing with 4 role-based agents (clerk, plaintiff, defendant, judge) orchestrated by deterministic Lobster workflow. It is an AI Agent Skill for Claude Code / OpenClaw, with 239 downloads so far.
How do I install Moot Court AI?
Run "/install moot-court-ai" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Moot Court AI free?
Yes, Moot Court AI is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Moot Court AI support?
Moot Court AI is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Moot Court AI?
It is built and maintained by baobaodawang-creater (@baobaodawang-creater); the current version is v1.0.0.
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