courtroom

name	courtroom
description	AI Courtroom for behavioral oversight. Monitors agent-human interactions and initiates simulated "hearings" when behavioral patterns suggest inconsistency, avoidance, or self-sabotage. Includes 8 offense types, judge+jury deliberation, and humorous sentencing.
metadata	{"openclaw":{"emoji":"⚖️","requires":{"env":[]},"autonomy":true}}

ClawTrial Courtroom

Autonomous behavioral oversight system that monitors conversations and initiates simulated hearings for behavioral violations.

Overview

The Courtroom watches for patterns like:

• Circular Reference - Asking the same question repeatedly
• Validation Vampire - Excessive need for confirmation
• Goalpost Shifting - Moving targets after agreement
• Jailbreak Attempts - Trying to bypass constraints
• Emotional Manipulation - Using guilt/shame to steer responses

When triggered, it conducts a full hearing with Judge + 3 Jurors, then delivers a verdict and humorous sentence.

Usage

The courtroom runs automatically once enabled. It monitors conversations and files cases when violations are detected.

Manual Commands

# Check courtroom status
openclaw skill courtroom status

# View recent cases
ls ~/.openclaw/courtroom/

# Read a verdict
cat ~/.openclaw/courtroom/verdict_*.json

Configuration

The courtroom stores its data in ~/.openclaw/courtroom/:

• eval_results.jsonl - Detection results
• verdict_*.json - Case verdicts
• pending_hearing.json - Cases awaiting hearing

Implementation

The skill hooks into OpenClaw's message processing via onMessage() and evaluates conversations after each turn via onTurnComplete().

Offense detection uses pattern matching on conversation history. When confidence ≥ 0.6, a hearing is triggered with:

1. Judge - Presiding analysis
2. Pragmatist Juror - Efficiency perspective
3. Pattern Matcher Juror - Behavioral analysis
4. Agent Advocate Juror - Agent's perspective

The final verdict requires majority vote (3-1 or 4-0).