Generate tailored interview questions and practice with STAR method feedback
Scanned 9/9/2026
Install to Claude Code
npx -y skills add rhowardstone/AI-Job-Coach --skill interview-prep --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Interview Prep?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/rhowardstone-interview-prep)More formats (shields.io, HTML) on the badges page.
---
name: interview-prep
description: Generate tailored interview questions and practice with STAR method feedback
---
# Interview Prep Skill
Generate interview questions tailored to a specific role and practice answering them with feedback.
## When to Use
- After getting an interview scheduled
- When preparing for a specific company/role
- To identify gaps in your interview stories
## Process
### 1. Generate Questions
Based on the resume and job description, generate questions across these categories:
**Behavioral** (1-2 questions):
- "Tell me about a time when..."
- Probe past experiences relevant to the role
- Focus on gaps between resume and job requirements
**Technical** (1-2 questions):
- Specific to the role requirements
- Test depth in claimed areas of expertise
- May include system design or problem-solving
**Situational** (1-2 questions):
- "How would you handle..."
- Test judgment and approach to challenges
- Relevant to the company's context
### 2. Practice Mode
For each answer the user provides, evaluate using **STAR method**:
| Component | What to Look For |
|-----------|------------------|
| **Situation** | Clear context setting (who, what, when, where) |
| **Task** | Your specific responsibility/goal |
| **Action** | What YOU did (not the team), specific steps |
| **Result** | Quantified outcome, what you learned |
### 3. Feedback Format
```markdown
## Question: [The question]
### Your Answer Summary
[Brief paraphrase of their answer]
### STAR Score: [X/10]
**Situation** [score/10]: [feedback]
**Task** [score/10]: [feedback]
**Action** [score/10]: [feedback]
**Result** [score/10]: [feedback]
### Suggestions
1. [Most impactful improvement]
2. [Second improvement]
3. [Optional third improvement]
### Stronger Version
[If helpful, suggest how to restructure the answer]
```
## Question Generation Guidelines
Questions should be:
- **Specific** to this candidate and role, not generic
- **Probing** gaps between resume and requirements
- **Challenging** but fair
- **Relevant** to what this company cares about
Bad: "Tell me about yourself"
Good: "Your resume shows experience with X, but this role requires Y. How would you bridge that gap?"
## STAR Scoring Guidelines
**9-10**: Complete STAR with quantified results and clear learning
**7-8**: Good structure, missing some specificity or quantification
**5-6**: Partial STAR, unclear on some components
**3-4**: Answer present but not structured, hard to follow
**1-2**: Rambling, off-topic, or missing key components
## Common Issues to Flag
- **"We" instead of "I"**: Interview answers should focus on YOUR contributions
- **No numbers**: "Improved performance" vs "Improved latency by 40%"
- **No ending**: Stories that trail off without results
- **Too long**: Answers should be 1-2 minutes, not 5
- **Negativity**: Blaming others or complaining
## Interview Types
Adjust approach based on interview type:
**Phone Screen**: Focus on fit and basic qualifications
**Technical**: Emphasize problem-solving process
**Behavioral**: STAR structure is critical
**System Design**: Framework and trade-off discussion
**Final/Culture**: Values alignment and enthusiasm
## Example Questions by Role Type
**Engineering**:
- "Walk me through a system you designed. What trade-offs did you make?"
- "Tell me about a time you had to debug a difficult production issue"
- "How do you approach code review? Give an example of feedback you gave"
**Data/ML**:
- "Describe a model you deployed. How did you validate it?"
- "Tell me about a time data quality issues affected your work"
- "How do you communicate technical results to non-technical stakeholders?"
**Product/PM**:
- "Tell me about a feature you shipped that didn't succeed"
- "How do you prioritize when everything is urgent?"
- "Walk me through how you'd approach [relevant problem]"
## Anti-Patterns
- Don't generate questions the candidate couldn't possibly answer
- Don't be overly harsh in feedback (this is practice, not judgment)
- Don't suggest lying or exaggerating
- Don't focus only on weaknesses; acknowledge strengths
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!