mcpbeat Sign in

Interview System Designer Skill for Claude

> Design calibrated interview loops, competency-based question banks, and hiring calibration. Use when designing interview processes, creating hiring pipelines, generating scoring rubrics, analyzing interviewer bias, or building question banks.

76k tokens
context cost
the whole folder, loaded on every use
16
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
447
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/borghei/Claude-Skills --skill interview-system-designer

What comes with it

295 765 bytes besides the instruction
README.md
assets/sample_interview_results.json
assets/sample_role_definitions.json
expected_outputs/product_manager_senior_questions.json
expected_outputs/product_manager_senior_questions.txt
expected_outputs/senior_software_engineer_senior_interview_loop.json
expected_outputs/senior_software_engineer_senior_interview_loop.txt
hiring_calibrator.py
loop_designer.py
question_bank_generator.py
references/bias_mitigation_checklist.md
references/competency_matrix_templates.md
references/debrief_facilitation_guide.md
references/tool-reference.md
references/workflows-and-templates.md

The instruction itself

8 sections, as written by the author

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 |

Other skills for the same job

different authors, same section of the catalogue
Protocolsio Integration
by christophacham
×4

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

16k tokens
Tailored Resume Generator
by frostant
×4

Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances

3k tokens
Excalidraw Diagram Generator
by github
vendor ×3

Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.

36k tokens scripts
Expo Dev Client
by openai
vendor ×3

Build and distribute Expo development clients locally or via TestFlight

961 tokens
Executing Plans
by ZhanlinCui
×3

Use when you have a written implementation plan to execute in a separate session with review checkpoints

542 tokens
Anndata
by christophacham
×3

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

16k tokens
Benchling Integration
by christophacham
×3

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

14k tokens
Biopython
by christophacham
×3

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

24k tokens

How to use it

Copy the folder

Take borghei/interview-system-designer from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.