sensei

Best report selection: Report 3 is the strongest and most accurate overall because it identifies the unusual credential repurposing (gh token -> OPENAI_API_KEY) and clearly ties it to likely downstream remote inference, while also noting a frontmatter parsing anomaly (correctness, not malware). Improved finding: This module itself does not show classic malware behaviors, but optimize_skill() creates a high-sensitivity credential flow: it harvests a GitHub token via `gh auth token`, repurposes it as an OpenAI API key, sets a remote inference endpoint, and then passes repository content to an external optimizer/LLM client. Review gepa/LLM client behavior, token scope/format, and ensure sensitive content is not sent unintentionally; also consider fixing the frontmatter parsing logic to avoid incorrect scoring/optimization inputs.