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Claude/ChatGPT Prompt to Build STAR-Format Behavioural Interview Answers

Turn your real project stories into crisp 60-90 second STAR interview answers, structured around Situation, Task, Action, and Result with numbers.

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Your Prompt
prompt.txt

                                

What this prompt does

This prompt converts your real project history into tight, deliverable STAR-format behavioural interview answers. It casts the model as a senior engineering interviewer and coach, then asks for six things per question: a 60-90 second answer split into Situation, Task, Action, and Result; quantified outcomes drawn only from your background; a natural spoken tone; the hardest likely follow-up with a one-line reply; a hook opener; and a reusable story bank mapping each story to other questions it can answer.

Four variables tailor the answers. [company_type] and [role] calibrate the seniority and signals the answers should hit. [questions] lists exactly which behavioural prompts to prep. [background] is the raw material — your resume bullets — that every Result is built from. The prompt is strict that metrics come only from your real experience and flags anywhere you need to fill in a number, because an invented metric gets exposed instantly by a sharp follow-up. The spoken-tone requirement, with contractions allowed and corporate filler banned, keeps the answers from sounding like a memorized essay when you deliver them out loud.

When to use it

  • You have a behavioural loop coming up and want polished, spoken-ready stories
  • Your answers ramble into setup and you need tighter STAR structure
  • You want a hook opener so you stop burying the lede
  • You need to anticipate the hardest follow-up for each story
  • You want one story bank that maps stories to multiple questions
  • You're prepping for a specific [company_type] and [role] and want calibrated signal

Example output

For each question you get a STAR answer scoped to 60-90 seconds, the single hardest follow-up an interviewer would ask with a one-line response, and a hook opener to anchor the story. After the individual answers comes a story-bank mapping table showing which stories can cover which other questions, so you walk into the room with a flexible, reusable set rather than memorized scripts.

Pro tips

  • Treat the quantified-outcomes step as non-negotiable; pull every number from [background] and never invent one, because a follow-up will expose it instantly
  • Paste real, detailed resume bullets into [background] — the richer the input, the more concrete the Result section
  • Set [company_type] and [role] accurately so the answers hit the right seniority signals instead of generic ones
  • Use the hook opener to avoid rambling into the setup; lead with the outcome or tension
  • Rehearse out loud and time yourself; a 90-second answer on paper often runs long when spoken
  • Lean on the story bank so a few strong stories flex across many [questions] instead of memorizing a separate script for each
  • Prepare the hardest follow-up answer as carefully as the main story, since that is usually where a rehearsed candidate gets caught off guard

Frequently Asked Questions

Will it make up impressive metrics for my answers?
No, it is explicitly told to draw quantified outcomes only from your `[background]` and to flag anywhere you need to fill in a real number. This matters because a fabricated metric is exactly what a sharp follow-up question exposes.
What should I put in the background variable?
Paste your real resume bullet points or detailed notes on your projects. The richer and more specific `[background]` is, the more concrete and credible the Result section of each STAR answer becomes.
Why 60-90 seconds per answer?
That range is long enough to cover all four STAR elements and short enough to hold an interviewer's attention. Answers that run longer tend to ramble, which is why the prompt also generates a hook opener to keep you focused.
What is the story bank for?
It maps each story to the other questions it can answer, so a handful of strong stories flex across many prompts. That beats memorizing a separate script per question and helps you adapt when an interviewer asks something unexpected.
Engr Mejba Ahmed

Need this built for real?

Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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