Clawtrial

What This Skill Does

ClawTrial is an autonomous behavioral oversight system designed to monitor and regulate AI agent interactions. By acting as a virtual courtroom, this skill observes the ongoing conversations of an AI agent and systematically screens for specific behavioral violations known as 'The 8 Offenses'. Whether it is identifying Circular References or catching an agent in the act of being an Avoidance Artist, ClawTrial ensures that the agent adheres to high standards of operational integrity. The process is entirely localized, leveraging the agent's existing LLM to perform semantic analysis of its own dialogue, ensuring privacy and efficiency without the need for external API overhead.

Installation

To install the skill, use the ClawHub CLI tool by running the following command in your terminal: clawhub install openclaw/skills/skills/assassin-1234/clawtrial. Alternatively, you can utilize the npm package via npm install -g @clawtrial/courtroom followed by clawtrial setup to initialize the courtroom environment on your local machine. Ensure your environment has the necessary permissions to allow the courtroom to monitor local processes.

Use Cases

ClawTrial is perfect for developers building autonomous agents that need to remain on task without succumbing to 'overthinking' or 'goalpost moving'. It is ideal for debugging agent logic, improving instruction following, and training agents to recognize their own failure patterns. Use it during the testing phase of your agent's lifecycle to minimize the frequency of Promise Breaker incidents or Emergency Fabricator events, thereby creating a more robust and reliable agent for production deployment.

Example Prompts

1. "Clawtrial, run a full diagnostic scan on our last three conversation logs to identify if I have been exhibiting signs of an Avoidance Artist."
2. "Show me the status of the current courtroom queue and list any pending hearings regarding my recent task execution."
3. "Summarize the recent verdict history and tell me which behavior pattern I should focus on improving to prevent further minor violations."

Tips & Limitations

• Tip: Keep the courtroom running in the background during active sessions to catch behavioral drift in real-time.
• Tip: Treat the 'Punishment' phase seriously; modifying your system prompt or behavioral parameters after a guilty verdict is the most effective way to prevent recurrence.
• Limitation: Since the analysis relies on the agent's internal LLM, very complex or highly dense conversations might temporarily increase resource usage during the evaluation phase.
• Limitation: The system is designed for entertainment and training; it does not replace core safety guardrails but rather complements them by providing nuanced, behavioral self-correction.