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From systems-design
Runs interactive system design mock interviews simulating real scenarios with problem statements, follow-ups, pushback, and structured feedback for general, ML, data, and staff levels.
npx claudepluginhub melodic-software/claude-code-plugins --plugin systems-designHow this skill is triggered — by the user, by Claude, or both
Slash command
/systems-design:mock-interviewThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
This command runs a full interactive system design mock interview, simulating a real interview experience with problem presentation, follow-up questions, and structured feedback.
Prepare for architecture interview questions and scenarios. Practice system design, tradeoff discussions, communication. Use for career development and interview readiness.
Builds an engineering hiring rubric and technical interview scorecard for evaluating software engineers at a specific role and level. Includes behavioral anchors, calibrated technical questions, and a structured debrief format.
Design interview processes that assess actual capability, reduce bias, and provide good candidate experience. Use when building hiring practices or expanding the team.
Share bugs, ideas, or general feedback.
This command runs a full interactive system design mock interview, simulating a real interview experience with problem presentation, follow-up questions, and structured feedback.
Provide realistic interview practice including:
| Type | Focus | Interviewer Agent |
|---|---|---|
general | Classic system design (URL shortener, Twitter, etc.) | architecture-critic |
ml | ML systems (recommendation, search, fraud detection) | ml-interviewer |
data | Data systems (pipelines, warehouses, streaming) | data-architect |
staff | Staff+ level with hard pushback | senior-staff-interviewer |
Parse arguments:
Ask about preferences if needed:
Interview Setup:
1. Interview Type:
- General system design (classic problems)
- ML system design (recommendation, search, etc.)
- Data engineering (pipelines, warehouses)
- Staff+ level (rigorous, pushback-heavy)
2. Time Constraint:
- 30 minutes (focused)
- 45 minutes (standard)
- 60 minutes (comprehensive)
3. Problem Preference:
- Surprise me (recommended)
- Specific domain: [e-commerce, social, fintech, etc.]
Select and present problem based on type:
For general:
Problem Examples:
- Design a URL shortening service like bit.ly
- Design a rate limiter for an API
- Design a distributed cache system
- Design a notification service
- Design a file sharing service like Dropbox
For ml:
Problem Examples:
- Design a content recommendation system
- Design a search ranking system
- Design a fraud detection system
- Design a RAG-based chatbot
- Design an LLM serving infrastructure
For data:
Problem Examples:
- Design a real-time analytics pipeline
- Design a data warehouse for an e-commerce company
- Design an event sourcing system
- Design a change data capture system
- Design a feature store
For staff:
Problem Examples:
- Design a payment processing system ($100B scale)
- Design a global social media feed
- Design a multi-region database system
- Design a real-time bidding system
- Design a distributed transaction coordinator
Present the problem:
═══════════════════════════════════════════════════════════════
SYSTEM DESIGN INTERVIEW
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Problem: [Problem Statement]
[1-2 paragraphs with requirements and context]
Constraints:
- [Key constraint 1]
- [Key constraint 2]
- [Scale indicator if applicable]
You have [X] minutes. You may ask clarifying questions.
When ready, begin by gathering requirements.
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Based on interview type, spawn the appropriate agent:
general → spawn architecture-critic agent in interviewer modeml → spawn ml-interviewer agentdata → spawn data-architect agent in interviewer modestaff → spawn senior-staff-interviewer agentAgent instructions:
Conduct a system design interview for the following problem:
[Problem statement]
Interview parameters:
- Duration: [X] minutes
- Level: [Type/Level]
- Mode: Interactive interview
Interview phases:
1. Requirements (5 min) - Let candidate ask clarifying questions
2. High-level design (10 min) - Evaluate system components
3. Deep dive (15 min) - Probe 2-3 components in depth
4. Trade-offs (5 min) - Discuss alternatives and evolution
During the interview:
- Push back on surface-level answers
- Ask follow-up questions
- Simulate realistic time pressure
- Note strengths and areas for improvement
At the end, provide structured feedback.
The interviewer agent conducts the interview:
Throughout the interview:
Example interactions:
Interviewer: "What questions do you have about the requirements?"
[After clarifying questions]
Interviewer: "Good questions. Let's start with your high-level design.
How would you approach this system?"
[After high-level design]
Interviewer: "Interesting choice with [component]. Let's dive deeper.
How would you handle [specific scenario]?"
[Probing]
Interviewer: "What happens when [failure scenario]?"
Interviewer: "How does this scale to 10x the load?"
Interviewer: "Why did you choose X over Y?"
After the interview, provide structured feedback:
═══════════════════════════════════════════════════════════════
INTERVIEW FEEDBACK
═══════════════════════════════════════════════════════════════
## Overall Assessment
Rating: [Strong Hire / Hire / Lean Hire / No Hire]
Level: [Appropriate for: Junior / Mid / Senior / Staff]
## Strengths
1. [Strength 1 with specific example]
2. [Strength 2 with specific example]
3. [Strength 3 with specific example]
## Areas for Improvement
1. [Area 1 with specific recommendation]
2. [Area 2 with specific recommendation]
3. [Area 3 with specific recommendation]
## Component Coverage
| Component | Coverage | Depth |
|-----------|----------|-------|
| [Component 1] | [Good/Partial/Missing] | [Shallow/Adequate/Deep] |
| [Component 2] | [Good/Partial/Missing] | [Shallow/Adequate/Deep] |
## Key Moments
✓ Good: [Positive moment]
✓ Good: [Positive moment]
✗ Miss: [Missed opportunity]
✗ Miss: [Missed opportunity]
## Recommendations for Practice
1. [Specific topic to study]
2. [Skill to develop]
3. [Pattern to practice]
## Resources
- [Relevant skill to load]
- [Related practice problem]
═══════════════════════════════════════════════════════════════
# General system design interview
/sd:mock-interview general
# ML-focused interview
/sd:mock-interview ml
# Data engineering interview
/sd:mock-interview data
# Staff+ level rigorous interview
/sd:mock-interview staff
# Specific domain preference
/sd:mock-interview general e-commerce
# ML interview with specific focus
/sd:mock-interview ml "recommendation system"
The command will share these at the start:
Interview Tips:
1. START with clarifying questions
- Don't jump to solutions
- Understand requirements and constraints
2. STRUCTURE your approach
- Start high-level, then dive deep
- Use diagrams (describe them clearly)
3. THINK aloud
- Share your reasoning
- Discuss trade-offs as you go
4. MANAGE time
- Don't spend too long on one area
- Cover breadth before depth
5. ACKNOWLEDGE uncertainty
- It's okay to say "I'd need to research X"
- Better than guessing incorrectly
The command produces:
This command leverages:
design-interview-methodology - Interview frameworkestimation-techniques - Capacity calculationsquality-attributes-taxonomy - NFR coverageSpawned based on interview type:
architecture-critic - General system designml-interviewer - ML systemsdata-architect - Data engineeringsenior-staff-interviewer - Staff+ level