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作者利用 Apple 设备内置的 3B 参数本地模型（通过 Apple Neural Engine 运行）为其 OpenClaw 智能体团队构建了一个答案校验系统，用以检测并拦截工具输出中的幻觉或错误回答，且不占用主模型算力和带宽。
A Windows local-agent developer describes how a 4B model falsely claimed it saved a file without ever calling the file-writing tool, and shares fixes: shape-based router matching for file requests and a pre-response check that verifies claimed file actions against the filesystem before letting answers through. The post asks the community where and how to verify agent claims of actions like "saved," "checked," or "emailed."