interview-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). 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 rubric and calibration guide are sibling skills in this plugin.

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, and (d) a structured output ready to drop into a hiring loop.

When to use

• A new QA / SDET / test-lead / quality-manager req has been opened and the team needs a question bank before scheduling interviews.
• An existing question bank is stale and the team is recalibrating after a hiring round.
• A team is moving from unstructured interviews to structured ones (the validity uplift is the published reason - see Levashina et al. 2014, Personnel Psychology).

Do not use this skill to:

• Produce the scoring rubric - that is hiring-rubric-author.
• Produce the calibration guide / gold-standard answers - that is calibration-guide-author.
• Author non-QA-role questions (general engineering, product, design). The skill is QA-scoped.

Step 1 - Capture the role inputs

Required inputs:

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:

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:

• Type: technical / behavioral / scenario / system-design.
• Seniority anchor: which level the question is calibrated for; senior questions remain useful at staff+ but with deeper probes.
• Bloom's level (K1 - K4): K1 (remember) for fundamentals, K2 (understand) for explanation, K3 (apply) for situational execution, K4 (analyse) for synthesis. Bloom's levels are used by ISTQB to anchor question difficulty across the Foundation Level syllabus.
• ISTQB competency the question maps to (cite by stable ID; the ISTQB Foundation Level v4.0 syllabus is the canonical competency reference, though its specific URL drift means cite by syllabus version).
• STAR cues (for behavioral questions only) - per the STAR method, the interviewer listens for all four components; missing components prompt follow-up probes.
• Time budget in minutes.
• Follow-up probes - pre-authored so different interviewers don't drift into ad-hoc probing (the dominant source of interview noise per structured-interview research).

Step 4 - Tune the difficulty distribution

Bloom's taxonomy mix per seniority (default; configurable):

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:

1. Header: role, seniority, domain, total slots, mix summary.
2. Question slots 1 - N: per the format in Step 3.
3. Reading list for the candidate (optional): canonical references the candidate can prepare against - ISTQB Foundation Level syllabus, the team's testing handbook, etc. Always optional; avoid if the role advertises "no prep needed".
4. Hand-off block:

## 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 `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

Limitations

• The bank is not a substitute for technical screening. A take-home or coding round is still recommended for SDET / automation roles where hands-on code is load-bearing. The skill produces interview questions, not coding exercises.
• STAR cues are heuristics, not auto-scoring. The interviewer still has to listen and score. The cue list reduces variance but does not eliminate it.
• Bloom's levels are the ISTQB-canonical proxy, not a perfect difficulty measure. A K3 question can be more or less difficult than another K3 depending on the topic. Use the level as a coarse mix knob, not a fine-grained difficulty score.
• Locale / language localisation is the team's responsibility. Behavioral questions translated literally can lose nuance; the skill emits English-language defaults.
• Legal compliance varies by jurisdiction. Some questions (age, family, health) are illegal in some jurisdictions and merely poor practice in others. The skill includes a default forbidden-topics list (age, family status, religion, sexual orientation, disability, national origin, citizenship except where role-required) but the hiring team is responsible for jurisdiction-specific compliance - see legal-compliance-checker ecosystem.

Hand-off targets

• Score the questions consistently → hiring-rubric-author.
• Calibrate interviewers → calibration-guide-author.
• Compliance review of the question set → the team's legal / HR review (out of marketplace scope; flagged here so the hiring manager remembers).

References

• ISTQB Certified Tester Foundation Level v4.0 syllabus - competency areas (test design, test management, test process, defect management, tools); cite by stable syllabus version (v4.0, 2023): https://www.istqb.org/certifications/certified-tester-foundation-level
• ISTQB glossary - defect, defect-density, escaped-defect, test design technique (the canonical competency vocabulary): https://glossary.istqb.org/
• STAR behavioral interviewing method - Situation / Task / Action / Result framework: https://en.wikipedia.org/wiki/Situation,_task,_action,_result
• Structured interview research - Levashina et al. 2014 (Personnel Psychology) on the validity uplift from structured employment interviews; the methodological basis for this skill's "same questions, same order, same scoring" defaults.
• Bloom's taxonomy - K1 remember / K2 understand / K3 apply / K4 analyse - ISTQB-adopted cognitive-difficulty levels: https://en.wikipedia.org/wiki/Bloom%27s_taxonomy
• PractiTest 2026 State of Testing Report - hiring rubric / interview question generation cited as a high-adoption, low-risk AI use case for QA managers: https://www.practitest.com/state-of-testing/
• hiring-rubric-author, calibration-guide-author - sibling skills that complete the structured-interview triple.