interview-prep

Builds mock interview simulators with dynamic prompts, timers, and scorecards.

Updated Jul 10, 2026
One-click install
npx skills add https://github.com/SaberAloui/agri-hub --skill interview-prep-saberaloui
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: interview-prep
Source: https://github.com/SaberAloui/agri-hub/tree/main/.local/secondary_skills/interview-prep
Command: npx skills add https://github.com/SaberAloui/agri-hub --skill interview-prep-saberaloui

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Preparing for interviews at a specific company and role requires realistic practice, but generic question lists cannot adapt to different industries, markets, or languages. This Skill provides instructions for building a mock interview simulator that dynamically tailors questions, feedback, and scorecards to any company, role, and location the user enters. ## Core Features & Use Cases - Dynamic System Prompt Builder: Constructs interviewer prompts from user inputs (company, role, interview type, language, difficulty) so one simulator serves finance, consulting, tech, or general roles. - Three Interview Modes: Structured interviews with role-adapted question categories, consulting case interviews with market sizing and profitability scenarios, and behavioral-only STAR practice. - Scorecard 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 scorecard.

Frequently Asked Questions about interview-prep

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a mock interview simulator with AI?▼

Create a setup screen collecting company, role, interview type, and language, then build a dynamic system prompt from those inputs and pass it to the conversation API. The AI acts as an interviewer at that company, asks one question at a time, and delivers a final scorecard.

How to make interview questions adapt to a specific company and role?▼

Construct the system prompt dynamically with the company name, role, and market context the user enters, instructing the AI to incorporate company knowledge and role-specific question categories. Never hardcode questions to one company or industry.

What interview types should a mock interview app support?▼

Support three modes: structured interviews mixing behavioral, technical, and firm knowledge questions; consulting case interviews covering market sizing, profitability, and market entry; and behavioral-only sessions focused on STAR-method storytelling practice.

Can the interview simulator conduct interviews in Spanish or other languages?▼

Yes, place an explicit language instruction at the top of the system prompt directing all questions, feedback, and the scorecard into the selected language. The UI chrome stays in English, and the AI should accept English technical terms like LBO or EBITDA without penalty.

How do I render the final interview scorecard in React?▼

Detect the scorecard in the AI's markdown response and parse it into a styled card showing the overall hire rating, category scores, top strengths, improvement areas, and response time summary. Use react-markdown with remark-gfm for rendering.

Why should the system prompt be hidden from the chat display?▼

The system prompt contains interviewer instructions, not conversation content, so showing it breaks immersion. Filter messages by role, checking m.role === "system", before rendering the chat message list.