interview-question-author
Build-an-X workflow that produces a QA-role-specific interview question bank - takes a role description (manual QA / SDET / automation engineer / test lead / quality manager) plus competency model and emits a structured question bank covering technical, behavioral (STAR-format), scenario-based, and system-design dimensions, classified by ISTQB-canonical competency areas and Bloom's taxonomy difficulty levels. This produces the questions only - not the scoring rubric and not the gold-standard answer guide. Use as the first artifact a hiring manager produces when opening a QA / test role, before scheduling the first interview.
Install with skills.sh (any agent)
npx skills add testland/qa --skill interview-question-authorinterview-question-author
Overview
Hiring for QA roles is calibration-heavy: the same question scored by two interviewers without a rubric produces high noise (well-documented in structured-interview research (opens in new window)). The remedy is a structured interview - same questions, same order, same scoring rubric across candidates. This skill produces the questions half of that pair; the scoring rubric and the calibration guide are separate artifacts.
The skill is QA-specific by design. Generic interview-question generators exist in the wider AI tooling space; the differentiation here is (a) ISTQB-aligned competency framing, (b) role-specific question depth (manual QA vs SDET vs test lead require different technical / behavioral mixes), (c) STAR-format anchoring on behavioral questions per the canonical STAR method (opens in new window), and (d) a structured output ready to drop into a hiring loop.
When to use
Do not use this skill to:
Step 1 - Capture the role inputs
Required inputs:
| Input | Notes |
|---|---|
| Role title | One of: manual-qa-engineer, qa-automation-engineer, sdet, test-lead, quality-manager. Each has different default depth weights (Step 3). |
| Seniority | One of: junior, mid, senior, staff+. Drives Bloom's-taxonomy difficulty mix in Step 4. |
| Domain context | The product area / regulated industry (e.g., "fintech payments", "healthcare EHR", "consumer mobile") - drives scenario-based questions. |
| Required competencies | Optional; if absent, the skill defaults to ISTQB Foundation Level chapters relevant to the role (test design, test management, test process, defect management, tools). |
| Forbidden topics | Optional; topics already covered elsewhere in the loop or out-of-scope for legal / compliance reasons. |
If the role title is not one of the five recognised QA roles, the skill halts with UNRECOGNISED_ROLE: supply a role from the recognised list, or run with role=qa-generic to use a flat default mix.
Step 2 - Allocate question slots
A typical 60-minute interview holds 6 - 8 questions. The skill defaults to a six-question shape. The mix shifts per role:
| Role | Technical depth | Behavioral (STAR) | Scenario-based | System / framework design |
|---|---|---|---|---|
| manual-qa-engineer | 2 | 2 | 2 | 0 |
| qa-automation-engineer | 3 | 1 | 1 | 1 |
| sdet | 2 | 1 | 1 | 2 |
| test-lead | 1 | 3 | 1 | 1 |
| quality-manager | 0 | 4 | 1 | 1 |
The mix is configurable; the table is the default. Behavioral count grows with seniority and people-leadership scope per the structured-interview research; technical depth grows with hands-on coding scope.
Step 3 - Author per-slot questions
For each slot, the skill emits one question with the metadata reviewers need:
### Q3 - Behavioral (STAR) | Senior | Bloom: K3 (Apply)
**Question:** Tell me about a release where you caught a critical defect late - after the test cycle but before production. Walk me through the situation, what your role was, what you did, and what the team learned.
**ISTQB competency:** Defect management (defect → failure distinction, escape-defect lifecycle).
**STAR cues:** Listen for: (S) the release context, (T) the candidate's specific responsibility, (A) the diagnostic and communication actions taken, (R) measurable outcomes + retro learnings.
**Time budget:** 8 min.
**Follow-up probes** (use only if the answer is shallow):
- "Was the defect found through automated tests, manual exploration, or a customer report?"
- "What changed in your team's process after this incident?"
- "How did you handle the stakeholder communication?"Each question carries:
Step 4 - Tune the difficulty distribution
Bloom's taxonomy mix per seniority (default; configurable):
| Seniority | K1 | K2 | K3 | K4 |
|---|---|---|---|---|
| junior | 30% | 40% | 25% | 5% |
| mid | 15% | 35% | 35% | 15% |
| senior | 5% | 25% | 40% | 30% |
| staff+ | 0% | 15% | 35% | 50% |
The skill flags questions whose Bloom's level is too far from the role's centre of gravity (e.g., a K1 fundamental question for a staff+ candidate is wasted slot).
Step 5 - Emit the bank
The output is a single markdown document with:
## HAND-OFF - required next steps
1. Pair with `hiring-rubric-author` to produce the per-question scoring rubric. The rubric and the questions must travel together; otherwise the loop reverts to unstructured.
2. Pair with `interviewer-calibration-guide-author` after the rubric exists; the calibration guide is what brings interviewer scoring into agreement.
3. Lock the question bank at the start of the hiring round; if the bank changes mid-round, every prior candidate's score is no longer comparable.Anti-patterns
| Anti-pattern | Why it fails | Fix |
|---|---|---|
| Generic behavioral questions ("Tell me about a time you faced a challenge") | Drains the slot; the answer is unscorable because the question lacks specificity. | Behavioral questions must name the QA-specific context (release, defect, framework, regulation). |
| Asking the same question across all seniority levels | The signal is wasted - a K1 fundamentals question reveals nothing about a staff+ candidate. | Step 4 difficulty tuning per seniority. |
| Including a question already covered in the take-home / coding screen | Double-coverage at the cost of a slot. | The forbidden topics input excludes those areas. |
| Including "puzzle" questions ("estimate the number of QA engineers in your city") | Validity is documented to be near zero per structured-interview meta-analyses; the question signals interviewer preference, not candidate competence. | The skill refuses to emit Fermi / puzzle questions. Cite structured-interview research (opens in new window) as the basis. |
| Behavioural questions without STAR cues for the listener | Different interviewers listen for different things; scoring drifts. | Step 3 STAR cues are mandatory for behavioural questions. |
| Letting interviewers free-form their own follow-ups | The dominant source of interview noise. | Step 3 pre-authored follow-up probes. |
| Authoring the question bank without the rubric | Half a structured interview - questions without scoring still drift. | Hand-off block insists on hiring-rubric-author next. |
Limitations
Hand-off targets
References
Related skills
hiring-rubric-author
Build-an-X workflow that produces a per-role QA hiring rubric - takes a role description (manual QA / SDET / automation engineer / test lead / quality manager) plus the question bank from `interview-question-author` and emits a competency-anchored scoring rubric with 4-level behavioral anchors (no-hire / borderline / hire / strong-hire) per competency. This produces the scoring scaffold only - not the questions themselves, and not the gold-standard model answers that demonstrate each score level. Use after the question bank exists and before the first interview is scheduled - the rubric is what brings interviewer scoring into agreement.
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Build-an-X workflow that produces an interviewer calibration guide for a QA hiring loop - takes the question bank and rubric (from sibling skills `interview-question-author` and `hiring-rubric-author`) plus 2-5 sample candidate transcripts/responses, and emits gold-standard model answers, common pitfalls, score-anchor examples per question, and a calibration-session script for the panel. Distinct from the question and rubric skills (which produce the questions and the scoring scaffold); this skill produces the **demonstration material** that brings two interviewers' scores into agreement. Use after the rubric exists and before the first real candidate - the calibration guide is what closes the inter-rater-reliability gap that the rubric alone cannot.
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qa-jd-author
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