摘要
arXiv:2603.16572v2 Announce Type: replace-cross Abstract: Agent skills extend local AI agents, such as Claude Code and OpenClaw, with additional functionality. Their growing popularity has led to dedicated marketplaces resembling mobile app stores, as well as automated scanners that assess whether skills are benign or malicious. However, scanner reports from individual marketplaces classify up to 46.8% of skills as malicious, raising concerns about false positives. We present the largest empirical security analysis of the AI agent skill ecosystem to date. We collect 238,180 unique skills from three major distribution platforms and GitHub, and analyze their contents, behavior, and repository context. Unlike existing scanner-based assessments, which evaluate skills largely in isolation, our repository-aware analysis checks whether a flagged skill is consistent with its surrounding GitHub project. This context substantially reduces the number of suspicious skills: only 0.
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