Build-an-X workflow that produces an interviewer calibration guide for a QA hiring loop - takes the question bank and rubric (from sibling skills `interview-question-author` and `hiring-rubric-author`) plus 2-5 sample candidate transcripts/responses, and emits gold-standard model answers, common pitfalls, score-anchor examples per question, and a calibration-session script for the panel. Distinct from the question and rubric skills (which produce the questions and the scoring scaffold); this skill produces the **demonstration material** that brings two interviewers' scores into agreement. Use after the rubric exists and before the first real candidate - the calibration guide is what closes the inter-rater-reliability gap that the rubric alone cannot.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The skill’s required workflow (Step 1) explicitly ingests “Sample transcripts (2–5 anonymised candidate transcripts … or recordings the panel has scored)” into the LLM context to generate gold-standard answers, and those transcripts are outsider-authored free text when they come from real candidates.