Interview System Designer

Design role-specific interview loops, generate competency-based question banks with scoring rubrics, and detect interviewer bias through statistical calibration analysis.

Core Capabilities

• Interview loop design — role/level/team-specific loops with rounds, time allocations, interviewer skill requirements, and scorecard templates.
• Question bank generation — competency-based questions with 1-4 scoring rubrics, follow-up probes, and poor/good/great calibration examples.
• Hiring calibration — statistical bias and drift detection across interviewers and time periods, with coaching recommendations.
• Scoring & benchmarks — 4-point rubric, target score distribution (20/40/30/10), interviewer-consistency and pass-rate benchmarks.
• Loop templates — junior/senior/staff+ engineering loops plus sample questions by level and STAR behavioral prompts.
• Bias guardrails — anti-pattern catalog (halo effect, similarity bias, unstandardized loops) and mitigation practices.

When to Use

• Designing an interview process or end-to-end hiring pipeline for any seniority level.
• Building a competency-based question bank with scoring rubrics.
• Generating scorecards, debrief guides, or interviewer assignments.
• Analyzing interviewer bias or calibration drift across candidates and time.

Clarify First

Before designing, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• Task — design an interview loop, generate a question bank, or calibrate hiring (selects loop_designer.py vs question_bank_generator.py vs hiring_calibrator.py)
• Role & level — the role and seniority (junior/senior/staff+) (drives loop rounds, time allocation, and rubric calibration via --role/--level)
• Competencies — which competencies the loop or questions must cover (sets --competencies and the question-bank scope)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Tools

The Python tools live at the skill root (not in scripts/). All support --help, JSON/text output.

Tool	Purpose	Command
loop_designer.py	Generate a calibrated interview loop (rounds, time, scorecards)	python loop_designer.py --role "Senior Software Engineer" --level senior --team platform --output loops/
question_bank_generator.py	Generate competency-based questions with rubrics + calibration examples	python question_bank_generator.py --role "Frontend Engineer" --competencies react,typescript,system-design --num-questions 30
hiring_calibrator.py	Detect bias/calibration drift across interviewers and periods	python hiring_calibrator.py --input interview_data.json --analysis-type comprehensive --trend-analysis

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

• references/workflows-and-templates.md — quick start, the 3 core workflows (design loop / generate bank / calibrate bar) with validation checkpoints, engineering loop templates, sample questions, the scoring rubric + calibration benchmarks, and the anti-pattern list. Read when designing a loop or applying the rubric.
• references/tool-reference.md — full flag tables, examples, and output formats for all three tools, plus a troubleshooting table and the success-criteria bar. Read when invoking the tools or debugging output.
• references/competency_matrix_templates.md — competency matrix templates per role family and level. Read when defining the competencies a loop must cover.
• references/debrief_facilitation_guide.md — structured debrief facilitation guide. Read when running the post-loop debrief and consolidating scores.
• references/bias_mitigation_checklist.md — interview bias mitigation checklist. Read when reviewing a loop or panel for fairness.

Scope & Limitations

This skill covers:

• Designing end-to-end interview loops for engineering, product, design, and data roles across all seniority levels (junior through principal)
• Generating competency-based question banks with structured scoring rubrics and calibration examples
• Detecting statistical bias and calibration drift across interviewers and time periods
• Producing scorecard templates, debrief guides, and interviewer assignment recommendations

This skill does NOT cover:

• Applicant tracking system (ATS) integration, job posting, or candidate sourcing pipeline management — see hr-operations/talent-acquisition
• Compensation benchmarking, offer negotiation strategy, or total rewards analysis — see hr-operations/hr-business-partner
• Workforce planning, headcount modeling, or organizational design — see hr-operations/people-analytics
• Post-hire onboarding program design or new-hire ramp-up tracking — see engineering/codebase-onboarding

Integration Points

Skill	Integration	Data Flow
hr-operations/talent-acquisition	Feed designed interview loops and scorecards into the talent acquisition pipeline for end-to-end hiring execution	Loop JSON output → talent acquisition workflow input
hr-operations/people-analytics	Supply calibration reports and interviewer performance data for workforce-level hiring analytics	Calibrator JSON reports → people analytics dashboards
engineering/codebase-onboarding	Hand off hired candidate profiles and assessed competency gaps to onboarding plan generation	Scorecard results → onboarding skill-gap inputs
hr-operations/hr-business-partner	Provide interview quality metrics and pass-rate data to support hiring bar discussions with HR leadership	Calibration trend data → HRBP quarterly reviews
product-team	Align PM interview loop competencies with the product team's competency frameworks and role leveling guides	Competency matrix → PM loop designer --competencies input
engineering/pr-review-expert	Use coding round evaluation criteria to inform code review standards for new hires during their ramp period	Scoring rubric technical criteria → PR review checklist alignment