Missing User Warnings
Medium
- Confidence
- 89% confidence
- Finding
- The code serializes and persists the full LLM input payload to disk, including engineer identifiers and bounded raw PR review/comment excerpts. In this skill's context, those excerpts can contain internal code-review discussion, project details, or sensitive employee-performance signals, so writing them to a local file creates a durable data-exposure surface beyond the immediate model call. The lack of disclosure or consent at the write site increases the risk of unexpected retention and downstream access by other users, tools, backups, or logs.
