What problem does it solve? Preparing for job interviews requires realistic practice tailored to a specific company, role, and industry, but generic question lists cannot adapt to each candidate's target. This Skill provides instructions for building a mock interview simulator that dynamically adapts questions, feedback, and scoring to any company, role, market, and language. ## Core Features & Use Cases - Dynamic Interview Generation: Builds a system prompt from user inputs (company, role, industry, difficulty, language) so the AI acts as an informed interviewer at that specific company. - Three Interview Modes: Structured interviews (behavioral, technical, firm knowledge), consulting case interviews (market sizing, profitability, M&A), and behavioral-only STAR practice. - Scoring & Feedback: Per-answer ratings, a response timer with color-coded pacing cues, and a final scorecard with overall hire rating, category scores, strengths, and improvement areas. - Use Case: A candidate targeting a Private Equity Principal role at Goldman Sachs enters the company and role, selects a challenging structured interview in English, and receives LBO technical questions, deal experience follow-ups, and a final scorecard with interview-day recommendations. ## Quick Start Build a mock interview simulator with a setup screen for company, role, and interview type that generates a dynamic system prompt and ends with a scored performance scorecard.
