Use this skill when designing structured interviews, creating rubrics, building coding challenges, or assessing culture fit. Triggers on interview design, rubrics, scoring criteria, coding challenges, behavioral interviews, system design interviews, culture fit assessment, and any task requiring interview process design or evaluation criteria.
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Use this skill when designing structured interviews, creating rubrics, building coding challenges, or assessing culture fit. Triggers on interview design, rubrics, scoring criteria, coding challenges, behavioral interviews, system design interviews, culture fit assessment, and any task requiring interview process design or evaluation criteria.
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Interview Design
Structured interview design is the discipline of building hiring processes that
produce consistent, defensible, and predictive hiring decisions. The core insight
is that unstructured conversations are notoriously unreliable predictors of job
performance - structured processes with explicit rubrics dramatically improve
both accuracy and fairness. This skill covers the full lifecycle: scoping the
interview loop, writing rubrics, building coding challenges, calibrating
interviewers, and running debriefs that lead to confident decisions.
When to use this skill
Trigger this skill when the user:
Needs to design an interview loop or process for a role
Wants to create scoring rubrics or evaluation criteria
Asks how to build a coding challenge or take-home assignment
Needs help writing behavioral interview questions
Wants to design a system design interview round
Is trying to assess culture fit in a structured, defensible way
Needs to run calibration sessions with a panel
Asks how to run an effective debrief meeting
Do NOT trigger this skill for:
Preparing as a candidate to pass interviews (different audience, different goal)
Compensation benchmarking or offer negotiation (use a compensation skill instead)
Key principles
Structured beats unstructured - Consistent questions asked in the same order
with pre-defined scoring criteria outperform free-form conversations every time.
Interviewers who "go with their gut" introduce bias, not signal.
Score independently before debrief - Every interviewer must submit a written
score and evidence summary before the panel debrief. Verbal-only debrief allows
the first strong opinion to anchor everyone else. Written scores first.
Test for the actual job - Every interview exercise should map to a real task
the candidate will perform in the role. If a backend engineer will never sort
arrays on the job, don't test array sorting in isolation. Use job-relevant problems.
Rubrics prevent drift - Without a rubric, two interviewers evaluating the
same candidate will produce wildly different scores. A rubric aligns on what
"strong" and "weak" looks like before the first candidate walks in.
Debrief is where decisions happen - The debrief meeting is not a vote-counting
exercise. It is a structured discussion to surface new evidence, resolve
disagreements, and reach a confident collective judgment. The hiring manager owns
the final call.
Core concepts
Interview types map to different evaluation needs. Coding interviews assess
problem-solving and technical mechanics. System design interviews assess
architectural thinking at scale. Behavioral interviews (using STAR) assess past
behavior as a proxy for future behavior. Values/culture interviews assess alignment
with how the team operates. Take-homes assess real-world execution and follow-through.
Most loops include 3-5 rounds covering different dimensions so no single round
carries all the weight.
Rubric design is the practice of defining expected performance at multiple
levels (typically 1-4 or Strong No / No / Yes / Strong Yes) before interviews begin.
A good rubric specifies concrete behaviors, not adjectives. "Breaks problem into
subproblems, names variables clearly, asks clarifying questions before coding" is
a rubric. "Good technical skills" is not. See references/rubric-templates.md for
ready-to-use rubric templates.
Signal vs noise distinguishes real predictors of job performance from
irrelevant factors. Signal: how a candidate structures ambiguity, responds to
hints, explains trade-offs. Noise: how polished their communication style is,
whether they went to a brand-name school, how quickly they reached the solution.
Train interviewers to write down evidence (what the candidate said/did) rather
than impressions ("seemed smart").
Calibration is the practice of running mock interviews with known candidates
(or invented personas) so interviewers practice applying the rubric consistently
before live interviews begin. A calibration session where two interviewers score
the same response and then compare notes surfaces misalignment early.
Common tasks
Design a structured interview loop
Start by mapping the role's core competencies - typically 4-6 dimensions that
predict success. Common dimensions for engineering roles:
Dimension
Who covers it
Technical fundamentals
Coding round 1
System design / architecture
System design round
Problem-solving approach
Coding round 2
Collaboration / communication
Bar raiser or cross-functional
Values and culture
Hiring manager or peer
Past impact and trajectory
Behavioral / resume deep-dive
Rules for a well-designed loop:
Every dimension is covered by exactly one round (no redundancy)
No interviewer covers more than one dimension (keeps each fresh)
The loop can be completed in one business day on-site or two days virtual
Assign a "bar raiser" - someone outside the immediate team with veto power
Create scoring rubrics - template
Use a 4-level rubric for each dimension. The key is defining the middle levels
precisely - candidates cluster there, and those are the hard decisions.
Dimension: [Name, e.g., "Problem Decomposition"]
Weight: [High / Medium / Low]
4 - Strong Yes
Candidate independently breaks problem into clean subproblems. Names
intermediate data structures without prompting. Explains trade-offs of
multiple approaches before choosing. Handles edge cases proactively.
3 - Yes
Candidate breaks problem into subproblems with minor prompting. Solves
the core problem correctly. Handles most edge cases when prompted.
Explains the primary trade-off.
2 - No
Candidate solves simple version but struggles to generalize. Requires
significant prompting to identify subproblems. Misses important edge
cases. Does not discuss trade-offs unless directly asked.
1 - Strong No
Candidate cannot decompose the problem independently. Solution is
incorrect or incomplete. Does not respond to hints. Cannot explain
what their own code does.
See references/rubric-templates.md for complete rubrics for coding,
system design, behavioral, and culture fit rounds.
Build a take-home coding challenge
Take-homes reveal real-world execution that 45-minute whiteboard problems cannot.
Design one that:
Scopes to 2-3 hours max - Respect candidate time. If it takes a senior
engineer 2 hours, calibrate down. State the expected time in the instructions.
Uses a realistic problem - "Build a rate limiter for our API" beats
"implement a binary search tree." Domain-adjacent problems reveal how candidates
think about the actual work.
Provides a starter repo - Give candidates a repo with the scaffolding, CI,
and test runner already wired. Evaluating candidates on setup skills is noise.
Defines evaluation criteria upfront - Include a EVALUATION.md in the repo
that lists exactly what reviewers will look for: correctness, test coverage,
code clarity, README quality.
Has a follow-up interview - Schedule a 30-minute code walkthrough. This
prevents submitting work that isn't the candidate's own and surfaces how they
think about their own decisions.
Evaluation checklist for reviewers:
Does the solution solve the stated problem?
Are edge cases handled?
Is the code readable without explanation?
Are there tests, and are they meaningful?
Does the README explain design decisions?
Are there obvious improvements the candidate noted themselves?
Design behavioral interview questions - STAR format
Behavioral questions follow the pattern: "Tell me about a time when..." The
STAR framework (Situation, Task, Action, Result) gives candidates a structure
and gives interviewers a rubric for what a complete answer looks like.
Writing strong behavioral questions:
Anchor to a specific competency (e.g., "conflict resolution" or "driving
alignment without authority")
Phrase as past behavior, not hypothetical: "Tell me about a time you disagreed
with your manager" not "What would you do if..."
Prepare follow-up probes in advance
Competency
Primary question
Follow-up probe
Handling ambiguity
Tell me about a project where the requirements were unclear. How did you proceed?
What would you do differently?
Driving impact
Tell me about the highest-impact project you've worked on. What made it high-impact?
How did you measure that impact?
Conflict resolution
Tell me about a time you had a serious technical disagreement with a peer.
How was it resolved?
Prioritization
Tell me about a time you had more work than you could finish.
What did you drop, and how did you decide?
Ownership
Tell me about something that went wrong on a project you led.
What did you change afterward?
Scoring STAR responses:
Situation/Task - Is the context clear and relevant to the role?
Action - Did the candidate describe their specific actions (not "we")?
Result - Is there a concrete, quantified outcome?
Learning - Does the candidate show reflection and growth?
Design system design interviews
System design interviews assess whether a candidate can architect solutions for
real-world scale and ambiguity. The structure matters as much as the content.
Interview structure (45-60 minutes):
Requirements clarification (5-10 min) - Candidate should ask scoping
questions: scale, read/write ratio, latency requirements, consistency model.
Award signal for good questions, not just correct answers.
High-level design (10-15 min) - Candidate draws the major components
and data flows. Watch for separation of concerns and component boundaries.
Deep dive (15-20 min) - Interviewer picks one or two components to
explore in depth: database schema, caching strategy, failure modes.
Trade-offs and bottlenecks (5-10 min) - Candidate explains what they
would improve with more time, where the system might break, and why they
made specific choices.
Rubric signals to watch:
Does the candidate ask clarifying questions before whiteboarding?
Can they estimate load and justify their component choices with numbers?
Do they proactively identify single points of failure?
Can they explain the trade-off between consistency and availability?
Do they adjust the design when the interviewer changes a constraint?
Run calibration sessions
Calibration prevents rubric drift before it happens. Run one calibration session
per new interviewer and one per quarter for existing panelists.
Calibration session format (60 minutes):
Distribute a transcript or video of a mock interview (use a fabricated
candidate, never a real one without consent)
Each interviewer scores independently using the rubric - no discussion yet
Reveal all scores simultaneously (prevents anchoring)
Discuss every dimension where scores diverge by 2+ points
Reach consensus on the "correct" score and the reasoning
Document the calibrated examples as reference cases for future interviewers
Red flags indicating calibration is needed:
Two interviewers gave the same candidate a 4 and a 1 on the same dimension
An interviewer cannot cite specific evidence for their score
Scores correlate with candidate demographics, not candidate performance
The team has not hired anyone in 6 months despite many interviews
Conduct effective debriefs
The debrief is the most consequential 30-60 minutes in the hiring process.
Run it badly and you amplify bias. Run it well and you surface the truth.
Before debrief:
All interviewers submit written scorecards independently (hiring manager cannot
see scores until all are submitted)
Block 48 hours maximum between last interview and debrief
Debrief agenda:
Hiring manager reads all scorecards silently (5 min)
Each interviewer speaks to their dimension only - what evidence they saw,
what level they scored, why (2 min per interviewer, no interruption)
Open discussion on dimensions with significant disagreement
Hiring manager asks: "Is there anything about this candidate we have not yet
discussed that is relevant?"
Hiring manager states the decision and the primary evidence that drove it
Decision framework:
Any Strong No from a bar raiser or domain expert is a block unless directly
rebutted with evidence (not "they seemed nervous")
"Probably yes" is a No - only hire on conviction
Document the stated rationale in the ATS for every decision, hire or no-hire
Anti-patterns
Anti-pattern
Why it fails
What to do instead
Gut-feel interviews
Interviewers cannot separate "I like them" from "they can do the job." Correlates with affinity bias, not job performance
Use structured questions and rubrics; require evidence-based scorecards
Brainteaser questions
"How many golf balls fit in a school bus?" measures nothing relevant to engineering work. Banned at most major tech companies
Use problems derived from real work the candidate will actually do
Group debrief without written scores
First speaker anchors the group. Quieter interviewers defer. The decision reflects seniority, not evidence
Require independent written scorecards before any verbal discussion
Hiring bar creep
Interviewers gradually raise standards over months until no one is hireable, stalling team growth
Tie rubric levels to job requirements, not to the best candidate ever interviewed
Same-style duplication
Two rounds both test the same coding dimension because neither interviewer was briefed on coverage
Map each dimension to exactly one round before the loop starts
Culture fit as veto
"Not a culture fit" used as a catch-all rejection with no supporting evidence - often a proxy for bias
Define culture/values criteria explicitly in the rubric; require behavioral evidence
Gotchas
Rubrics calibrated only on strong candidates produce grade inflation - If interviewers see 10 qualified candidates in a row, their mental model of "a 3" drifts upward over time. Run calibration sessions quarterly using the same reference examples to anchor scores. Grade inflation causes you to reject good candidates because they score "only" a 3 when the bar has silently moved to 3.5.
Take-home exercises without a time cap select for availability, not skill - Without an explicit time cap, candidates who are between jobs or have no outside commitments will spend 12 hours on a "2-3 hour" challenge, and their submissions will look objectively better. State "we expect this to take 2-3 hours" in the instructions and calibrate your evaluation rubric to what a strong engineer can produce in that time.
Allowing the hiring manager to see scores before all interviewers submit creates anchor bias - If one interviewer submits a Strong Yes early and the hiring manager shares it in Slack, every subsequent scorer is subconsciously anchored. Enforce blind independent scoring: no interviewer sees anyone else's score or written feedback until all scorecards are submitted.
Interview loops covering the same dimension twice produce inflated confidence - Two coding rounds both asking algorithm questions don't double the signal - they create redundant data while leaving system design, communication, or values completely unevaluated. Map each round to a unique dimension before the first candidate interviews, and stick to the map.
Debrief dominated by the most senior person in the room is not a debrief - If an engineering director speaks first with a strong opinion, junior interviewers defer and the decision reflects the director's prior, not the collective evidence. The facilitator must ask every interviewer to present their evidence before any discussion begins, starting with the most junior voice.
References
For detailed content on specific topics, read the relevant file from references/:
references/rubric-templates.md - Ready-to-use scoring rubrics for coding,
system design, behavioral, and culture fit rounds
Only load a references file if the current task requires deep detail on that topic.
Companion check
On first activation of this skill in a conversation: check which companion skills are installed by running ls ~/.claude/skills/ ~/.agent/skills/ ~/.agents/skills/ .claude/skills/ .agent/skills/ .agents/skills/ 2>/dev/null. Compare the results against the recommended_skills field in this file's frontmatter. For any that are missing, mention them once and offer to install:
