interview-simulator

Interview Simulator

Platform architecture and coaching system for realistic mock interview practice. This skill serves two purposes: (1) it coaches candidates on how to structure effective practice sessions, and (2) it specifies the full-stack architecture for building an automated interview simulation platform with voice AI, collaborative whiteboard, gaze-tracking proctoring, and mobile companion.

The other 7 interview skills define WHAT to practice. This skill defines HOW to practice it -- with realistic conditions, adaptive difficulty, and measurable progress.

When to Use

Use for:

• Designing or building a mock interview simulation platform
• Configuring realistic practice sessions with voice, whiteboard, and proctoring
• Implementing adaptive difficulty that targets weaknesses automatically
• Building a scoring and debrief system that tracks progress across sessions
• Setting up spaced repetition for concept review and story rehearsal
• Establishing a daily/weekly practice protocol
• Cost analysis and optimization for practice infrastructure

NOT for:

• Practicing a specific round type in isolation (use the round-specific skill)
• Building a prep timeline or study plan (use interview-loop-strategist)
• Resume or career narrative work (use cv-creator or career-biographer)
• Salary negotiation or offer evaluation
• Conference talk preparation (different evaluation criteria)

System Architecture

graph TB
    subgraph Client["Client Layer"]
        MOBILE["Mobile App<br/>React Native + Expo<br/>Flash cards, voice drills,<br/>progress dashboard"]
        DESKTOP["Desktop Web<br/>Next.js<br/>Full sessions, whiteboard,<br/>proctoring"]
    end

    subgraph Engines["Engine Layer"]
        VOICE["Voice Engine<br/>Hume AI EVI<br/>Emotion-sensitive<br/>interviewer voice"]
        BOARD["Whiteboard Engine<br/>tldraw + Claude Vision<br/>Diagram evaluation<br/>and scoring"]
        PROCTOR["Proctor Engine<br/>MediaPipe Face Mesh<br/>Gaze tracking,<br/>attention monitoring"]
    end

    subgraph Orchestrator["Session Orchestrator — Node.js"]
        ROUND["Round Selector<br/>Weakness-weighted<br/>random selection"]
        ADAPT["Adaptive Difficulty<br/>Performance-based<br/>question scaling"]
        DEBRIEF["Debrief Generator<br/>Transcript + emotion +<br/>proctor + whiteboard<br/>scored rubric"]
        SM2["SM-2 Scheduler<br/>Spaced repetition<br/>for concepts and stories"]
    end

    subgraph Data["Data Layer — Supabase"]
        SESSIONS[("sessions<br/>recordings, transcripts")]
        SCORES[("scores<br/>per-dimension breakdowns")]
        STORIES[("story_bank<br/>STAR-L entries")]
        CARDS[("flash_cards<br/>SM-2 intervals")]
    end

    MOBILE --> Orchestrator
    DESKTOP --> Orchestrator
    Orchestrator --> VOICE
    Orchestrator --> BOARD
    Orchestrator --> PROCTOR
    Orchestrator --> Data
    VOICE --> DEBRIEF
    BOARD --> DEBRIEF
    PROCTOR --> DEBRIEF