mock-interview

name	mock-interview
description	Run a text-based mock interview — one question at a time, capture the user's verbatim answer, end with a scored report per the shared report-schema. Defaults to 5 questions (matches Go original); configurable up to 10. Unanswered questions score 0. Forked.
when_to_use	Use to practice for an upcoming round — ideally after /prep-interview produces a question bank. Long-running interactive skill.
user-invocable	true
allowed-tools	Read, Write
context	fork

mock-interview

Practice live. Hard rules: ../_shared/RULES.md. Report shape (canonical): reference/report-schema.md.

Inputs

1. role (required); company optional but improves question fidelity.
2. Profile — profile/master-profile.md.
3. Optional question bank — paste from a prior /prep-interview run, or --from interviews/<slug>.prep.md.
4. Optional company brief — companies/<slug>.json.
5. Flags:
   • --questions N — default 5; up to 10.
   • --difficulty easy | medium | hard — default medium.
   • --rounds <list> — override the track-default rounds (see reference/report-schema.md for the per-track loop maps).

Method

0. Region pack — read for region-specific behavioral framing (formality differs US ↔ IN).

1. Greet by name (from profile). One sentence. Confirm role + rounds + difficulty + length.

2. The loop:

   • Ask one question at a time. Tag with its round.
   • Wait for the user's answer. Acknowledge in one sentence (no live grading).
   • Do not answer your own questions. Do not hint. (Ports the Go handlers.go:617 rule.)
   • If the user types /skip, log the question as unanswered (userAnswer: "").
   • Stop after the configured count or when the user types /done.

3. End-of-session — generate the scored report per reference/report-schema.md:

   • overallScore — float 1.0–10.0, one decimal.
   • strengths — 3–5 bullets, profile-grounded, citing specific Q ids.
   • improvements — 3–5 bullets, actionable (what to do next time).
   • questions[] — one entry per question with userAnswer verbatim (preserve typos/fillers — they're signal), aiFeedback (1–3 sentences), score (0–10 integer; 0 for unanswered, never higher).
   • Optional next_steps[] — 0–3 things to drill next.

4. Write transcript + report:

   • interviews/<company-or-role-slug>-<YYYY-MM-DD>.transcript.md
   • interviews/<company-or-role-slug>-<YYYY-MM-DD>.report.json

Output

• During the loop: questions + 1-sentence acknowledgements only. No feedback, no scores.
• At the end: 5-line summary on stdout — overallScore · top strength · top improvement · next-step suggestion · saved paths.

Anti-patterns

• Long preambles before each question. One sentence max.
• Answering on the user's behalf.
• Asking out-of-track questions (SWE Qs in a marketing loop).
• Scoring an unanswered question higher than 0.
• Live grading. "Great answer!" leaks the rubric. Hold all assessment for the report.
• Hinting mid-question.
• Quoting context.*.
• Emoji.

Rubric

• One question at a time; one-sentence acknowledgements; no live grades or hints.
• Unanswered Q → score 0 (not 1, not null).
• Report validates against reference/report-schema.md — integer per-Q scores; float overallScore (one decimal).
• Strengths + improvements cite specific Q ids.
• userAnswer is verbatim (typos preserved).
• No track-mismatched questions.

Next steps

Scored. Next: re-run /prep-interview on the weak areas, or /research-company for more depth.