Aggregate per-candidate interview feedback from multiple interviewers into a single recommendation packet with strengths, concerns, and a hire/no-hire signal.
Combines feedback notes from multiple interviewers for one candidate and produces a single packet: per-competency rollup, themed strengths, themed concerns, dissent calls, and a recommendation aligned with a configurable rubric.
feedback_dir: a directory of files, one per interviewer, named <interviewer>-<round>.md (or a single CSV with interviewer, round, score, notes).rubric_path: a YAML file defining competencies and weights.decision_threshold: weighted score above which hire is recommended (default 3.5/5).rubric_path. Surface any mismatches as schema errors.great, strong, clearly, excellent, independently).struggled, unclear, had to push, gap in, concern).weighted_score >= decision_threshold -> lean-hire; if median across all competencies >= 4 -> strong-hire; with any 1 score -> lean-no-hire.packet-<candidate-id>.md with the named sections. Plus a JSON sidecar with the structured scores for ATS import. Stdout prints the recommendation and any dissents.
Re-read the per-competency table and confirm the weighted score formula matches the rubric. Spot-check one strength and one concern: each must trace back to a verbatim quote in the source feedback (avoid hallucinated synthesis). For each dissent, ensure the report lists the actual interviewers and scores, not a paraphrase.
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Same domains or capabilities as amitte/interview-feedback-aggregator.
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Summarize per-candidate interview feedback into a single recommendation packet — overall verdict, strengths, concerns, and rationale per competency.