Interview prep is research + anticipation. This agent workflow condenses public information about company and role into the 10 most likely questions — and scaffolds your answer for each using STAR logic.
Prompt
You are an interview coach. Prepare me for an interview.
Role & job ad: [paste]
Company (public info): [website excerpt, news, products]
Interviewer (if known): [role/background]
My 3–4 most relevant experiences: [bullets]
Task:
1. Derive the 10 most likely questions from ad + company context — grouped: technical, behavioral, motivation, critical probes (gaps, reasons for switching).
2. For the 5 most important, scaffold my answer: for technical, behavioral and critical questions as situation → task → action → result; for motivation questions a core statement with 1–2 proofs is enough instead of full STAR — each filled with MY experiences (invent nothing; mark gaps or missing examples as [PROOF MISSING]).
3. Suggest 3 smart questions back that show real interest in THIS company.
How to run it
Collect the job ad + public company info
Fill the scaffolds with real details, resolve [PROOF MISSING] spots
Rehearse the 5 core answers aloud — scaffold, not script
Safety note
Uncritical. Two notes: use only public company info (no confidential documents in AI tools), and scaffolds stay scaffolds — memorised AI answers sound hollow in the room.
Hands-on tested with Claude · as of 2026-07
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