Smart Scheduler

智能任务调度器 - 简单任务秒级响应，复杂任务深度思辨。自动识别任务复杂度，路由到最优处理器。集成苏格拉底探明、任务分解、资源定位、多模型辩论验证。

This skill is not clearly malicious, but it contains risky and inconsistent behavior compared to its SKILL.md claims. Specific concerns: (1) It writes temporary Python files and executes them with subprocess (python3.8) — that can run arbitrary code on your machine; (2) It contacts hardcoded local services (127.0.0.1:5000 and 127.0.0.1:8002) and external ClawHub URLs, despite claiming no unauthorized network requests; (3) It inspects your skills directory (/home/admin/.openclaw/...) and /proc/meminfo; (4) The SKILL.md asserts sandboxing and no hardcoded tokens, but the code does not implement a clear secure sandbox or use environment-configurable endpoints. Before installing or enabling this skill, consider: run it in an isolated/test environment (not on production machines); require the developer to make endpoints configurable via environment variables (no hardcoded URLs); disable or review the self-generate execution path (or restrict to a real sandboxed runtime/container); request proof or documentation of the claimed sandbox implementation; and audit the full, untruncated code for any other hidden behaviors. If you cannot get these mitigations, avoid installing on sensitive systems.

Type: OpenClaw Skill Name: openclaw-smart-scheduler Version: 1.0.1 The skill bundle implements a 'self-generation' feature in resource_locator.py that uses subprocess.run to execute dynamically generated Python code in a temporary file, which poses a significant risk of Remote Code Execution (RCE) if the agent's logic is subverted. It also interacts with local network services (127.0.0.1:8002) for 'debate verification' and reads system-level information from /proc/meminfo. While these features are consistent with the stated goal of a sophisticated task scheduler, the inclusion of arbitrary code execution and local network probing is high-risk behavior.