What problem does it solve?
Hiring panels waste 60+ minutes of debrief meeting time manually comparing per-interviewer scorecards and notes instead of discussing actual disagreements. This skill eliminates that friction by pre-synthesizing all scorecards into a structured, evidence-grounded brief that surfaces only the points the panel needs to resolve, while enforcing guardrails to avoid bias and regulatory non-compliance.
Core Features & Use Cases
- Structured scorecard aggregation: Aggregates per-interviewer scores against a role-specific rubric to calculate mean, range, and standard deviation per dimension, with breakdowns by interviewer role (hiring manager, peer, cross-functional, bar-raiser).
- Rule-based disagreement escalation: Automatically surfaces decision-points for the panel when score ranges exceed thresholds, bar-raisers dissent, or hiring managers have outlier high scores, per strict, auditable rules.
- Bias and compliance guardrails: Enforces minimum evidence note lengths, blocks auto-deciding hire/no-hire to comply with global hiring AI regulations, includes calibration checks against prior debriefs to catch scoring bias, and avoids paraphrasing evidence to prevent demographic inference leakage.
- Use Case: A hiring panel that just completed a full interview loop for a senior backend engineer role can use this skill to generate a pre-read debrief brief in minutes, so their synchronous meeting focuses only on resolving the 2-3 identified decision-points instead of rehashing already-consensus feedback.
Quick Start
Use the interview-debrief-summary skill to generate a pre-debrief brief for candidate ID 7890 using the provided senior backend engineer role rubric and their submitted interview scorecards, then save the output to the team's shared debrief folder.
