Interview Driven Learn

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name: interview-driven-learn description: "Interview-driven is all you need. Drives end-to-end tech learning with interview standards. Activated when the user submits study notes, project summaries, or technical concept explanations. Transforms any learning input into interview-ready output using a five-step process: (1) Feynman test (ELI5 + professional), (2) interview question generation with answer points and follow-up traps, (3) STAR story extraction, (4) analogical learning, (5) weakness diagnosis. Auto-maintains two reference documents: a Knowledge Base (learning timeline) and a Question Bank (all questions aggregated by topic for self-review). Designed for computer science students preparing for backend, algorithm, or system design interviews at top internet companies."

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Interview Prep

> Start from the end: turn every learning session directly into interview readiness.

Core Files

Knowledge Base: references/knowledge-base.md — appended with each new topic, recording the theme + learning timestamp

Question Bank: references/question-bank.md — all interview questions aggregated by topic for easy self-review

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Input

Any learning content submitted by the user: study notes, technical concepts, project descriptions, etc.

Output: Five-Step Process

For every input, execute the following five steps:

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Step 1 - Feynman Test (ELI5 + Professional)

Describe the concept in two ways:

ELI5: As if explaining to a 10-year-old

Professional: Complete, rigorous, no key details omitted

Purpose: Verify true understanding, not rote memorization.

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Step 2 - Interview Question Generation

Generate 5-8 high-frequency interview questions in three categories:

Fundamentals (what / differences / principles)

Deep Dive (why / how / tradeoffs)

Applied (examples / scenario-based)

Each question includes:

What it tests

Key answer points

Follow-up direction if answered incorrectly

→ Also append to question-bank.md (aggregated by topic)

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Step 3 - STAR Story Extraction

Break down the content into reusable STAR narratives:

Situation: Background (technical scenario / business constraints)

Task: Goal (what you needed to solve)

Action: What you specifically did

Result: Quantified outcomes + lessons learned

Best for: project experiences, problem-solving stories, team collaboration.

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Step 4 - Analogical Learning (One to Three)

Same-level analogy: What is this like in everyday life? What else works this way?

Deeper analogy: What is one level below this? What's the underlying principle?

Transfer analogy: Where else can this approach be applied?

Purpose: Build a knowledge network, not isolated facts.

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Step 5 - Weakness Diagnosis + Knowledge Archive

Proactively uncover vulnerabilities:

Where will interviewers probe until you can't answer?

What do you think is important but actually isn't?

What classic pitfalls remain unfilled? (edge cases, concurrency, distributed tradeoffs)

→ Append to knowledge-base.md with format:

## [Topic]
Learned at: YYYY-MM-DD HH:mm
Core takeaway: one-sentence summary
Weak spots to reinforce: [spot 1, spot 2, ...]

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Output Format Template

## 📚 Topic: [User's Input Topic]
1. Feynman Test
ELI5:
> [One-sentence version]
Professional:
> [Full description]
2. Interview Questions
| # | Question | Tests | Key Points |
|---|----------|-------|------------|
| Q1 |          |       |            |
Follow-up traps: ...
3. STAR Story
S: [Background]
T: [Goal]
A: [Action]
R: [Result + Reflection]
4. Analogical Learning
🔗 Same-level: ...
🔬 Deeper: ...
🚀 Transfer: ...
5. Weakness Diagnosis
⚠️ Likely follow-up pressure points:
1. ...
2. ...
*Synced to Knowledge Base & Question Bank*

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File Structure

interview-prep/
├── SKILL.md
└── references/
    ├── knowledge-base.md   # Learning timeline
    └── question-bank.md    # Interview questions by topic

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Trigger Words

When the user says/submits:

"I learned XXX today"

"Help me prepare for an interview"

"Generate interview questions from these notes"

"What interview questions can come from this concept"

"What questions can this project be asked"

→ Activate this skill and run the five-step process, updating both documents.