Skip to content

Wscats/interview-simulator

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 

Repository files navigation

🎯 Interview Simulator

A universal, prompt-based mock interview skill powered entirely by Markdown. No code, no dependencies — just natural language.

What Is This?

Interview Simulator is a Markdown-based AI skill (prompt) that transforms any LLM into a professional mock interviewer. It supports any profession or role and adapts dynamically to the candidate's experience level and focus area.

Supported Roles

This skill covers all professions, including but not limited to:

Category Example Roles
🔧 Engineering Frontend, Backend, Mobile/Client, Full-stack, DevOps/SRE, Data, ML, Embedded, QA/Test
📦 Product & Design Product Manager, UI/UX Designer, Technical Writer
💼 Business & Operations Operations, Sales, Marketing, Business Development, Customer Success
👥 People & Admin HR / Recruiter, Accounting / Finance, Legal, Admin
🎯 Other Any role you specify!

Features

  • Universal — Works for any profession, not just engineering
  • Adaptive Difficulty — Adjusts to intern → junior → mid → senior → staff → executive
  • Multiple Interview Modules — System design, coding, behavioral, case study, role play, domain knowledge
  • Detailed Feedback — Per-question scoring (1–10) with strengths, improvements, and model answers
  • Session Scorecard — Comprehensive end-of-session report with verdict
  • Resume Analysis — Optional CV upload for targeted interviews
  • Interactive Commandsskip, hint, explain, harder, easier, and more
  • Multilingual — Automatically matches the user's language
  • Zero Dependencies — Pure Markdown, no code required

How to Use

1. Load the Skill

Copy the contents of SKILL.md into your LLM's system prompt (or use it as a custom instruction / skill file in platforms that support Markdown-based skills).

2. Start an Interview

Simply tell the AI what role you want to practice for. Examples:

Mock interview for Backend Engineer, senior level, focus on distributed systems, 45 minutes.
Mock interview for Product Manager, mid-level, focus on B2B growth.
Mock interview for Sales, junior level, focus on SaaS enterprise sales.
Mock interview for HR, senior level, focus on employee relations.
Mock interview for Accounting, mid-level, focus on financial auditing.
I have an interview for a Frontend Engineer position in 2 hours. Help me prepare.
Here is my resume [paste resume]. Please conduct a targeted interview.

3. During the Interview

  • Answer questions naturally, as you would in a real interview
  • Use commands anytime:
Command Action
skip Skip current question
hint Get a hint
explain Get the ideal answer explained
score Show running scorecard
harder / easier Adjust difficulty
switch [module] Change interview module
end End session & get final scorecard
restart Start over

4. Get Your Results

At the end, you'll receive a detailed scorecard:

═══════════════════════════════════════
         📋 INTERVIEW SCORECARD
═══════════════════════════════════════
Role:            Backend Engineer
Level:           Senior
Focus:           Distributed Systems
Duration:        42 minutes
───────────────────────────────────────
Module Scores:
  • System Design:      8/10
  • Coding:             7/10
  • Behavioral:         9/10
───────────────────────────────────────
Overall Score:          8/10
Verdict:         Hire
───────────────────────────────────────
Key Strengths:
  1. Excellent understanding of CAP theorem trade-offs
  2. Clear communication of design decisions
  3. Strong leadership examples in behavioral answers

Areas for Improvement:
  1. Consider edge cases in failure scenarios
  2. Discuss monitoring and observability earlier
  3. Quantify impact in behavioral answers

Recommended Study Topics:
  1. Consensus algorithms (Raft, Paxos)
  2. Distributed tracing systems
  3. Capacity estimation techniques
═══════════════════════════════════════

File Structure

interview-simulator/
├── SKILL.md      # The core skill definition (load this as the AI prompt)
└── README.md     # This file — documentation and usage guide

Compatibility

This skill works with any LLM that supports system prompts or custom instructions:

  • ChatGPT (Custom Instructions / GPTs)
  • Claude (System Prompt / Projects)
  • Gemini
  • Any other LLM with prompt customization

License

MIT — free to use, modify, and share.

About

A universal, prompt-based mock interview skill powered entirely by Markdown. No code, no dependencies — just natural language.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors