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: Constructs 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. - Scorecards and Progress Tracking: Renders an end-of-session scorecard with hire ratings, category scores, strengths, and improvement areas, plus a response timer and stage-based progress sidebar. - 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 hire/no-hire scorecard. ## 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.
