Skill: depictlightning/interview-driven-learn (version 1.0.0)

--- 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." --- # 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 --- ## 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: --- ### 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. --- ### 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)** --- ### 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. --- ### 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. --- ### 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: ```markdown ## [Topic] - Learned at: YYYY-MM-DD HH:mm - Core takeaway: one-sentence summary - Weak spots to reinforce: [spot 1, spot 2, ...] ``` --- ## Output Format Template ```markdown ## 📚 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* ``` --- ## File Structure ``` interview-prep/ ├── SKILL.md └── references/ ├── knowledge-base.md # Learning timeline └── question-bank.md # Interview questions by topic ``` --- ## 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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)