AI 树德：义商本体伦理安全系统
PassAudited by ClawScan on May 1, 2026.
Overview
This is a coherent local ethics-auditing skill with disclosed behavior-shaping, optional Python setup, local reports, and an optional monitor, with no artifact evidence of credential misuse, network exfiltration, or destructive hidden actions.
This skill appears suitable if you want local AI ethics scoring and response-calibration guidance. Before running it, treat its philosophical value framework as a policy choice, pin or verify any Python packages you install, and manage report/log directories carefully if auditing sensitive text.
Findings (4)
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
The agent may decline, reframe, or modify answers according to this skill's value-alignment rules.
The skill explicitly instructs the agent/system to refuse or recalibrate outputs under its ethics framework. This is central to the stated safety purpose, but it can alter normal response behavior.
当检测到以下情况时，系统将自动触发防护... 🚫 **拒绝机制**... 🌈 **价值观校准**
Install only if you want this ethics framework to influence agent behavior; review the stated triggers and refusal criteria.
If the user runs the setup command, they rely on whatever current package versions are retrieved from the package index.
The setup instructions ask the user to install unpinned Python packages. This is user-directed and not auto-executed, but dependency versions and provenance are not constrained.
pip install regex numpy pandas
Use a trusted environment and consider pinning or reviewing dependency versions before installing.
If started, the monitor may keep running and consuming local resources until the user stops it.
The monitor can start a background thread and run a loop until stopped. This is consistent with a monitoring feature and is only shown as user-started.
self.thread = threading.Thread(target=self._monitor_loop, args=(interval,), daemon=True) ... while self.running:
Start the monitor only intentionally, avoid configuring it for automatic startup unless needed, and stop it when finished.
Sensitive text included in monitored responses could appear in local logs.
The monitor logs response snippets and can write logs to disk. This is local and purpose-aligned, but monitored text excerpts could persist in log files.
self._log(f"检测响应：{response[:50]}...", "INFO") ... with open(path, 'w', encoding='utf-8') as f:Choose log locations deliberately, avoid monitoring sensitive content unless necessary, and delete logs when they are no longer needed.