interview-prep

interview-prep is a command for Claude Code from MadeByTokens/resume-helper. It costs 7 tokens per session (1,136 once invoked), scanned A, original, MIT.

A command that creates an interview-preparation document from a resume. It generates likely questions about experience, technical details, behavior, career changes, and questions for the interviewer.

In plain words
What is it for?
Use it with a resume file, or with the resume from the last completed workflow. It produces preparation material organized by common interview question categories.
Why use it?
It turns the claims and details in a resume into focused topics to practise. This helps prepare for questions that explore whether the candidate can support or explain their stated experience.

Command for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the resume-helper plugin — 5 commands, 9 agents shipped together

Good fit Use it with a resume file, or with the resume from the…

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/madebytokens/resume-helper/interview-prep
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/MadeByTokens/resume-helper

Made for: Claude Code.

Or install resume-helper, the plugin that ships this one along with the rest of its 5 commands, 9 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for interview-prep

README.md
[![agentmods](https://agentmods.dev/badge/commands/madebytokens/resume-helper/interview-prep.svg)](https://agentmods.dev/commands/madebytokens/resume-helper/interview-prep)
Your own site
<a href="https://agentmods.dev/commands/madebytokens/resume-helper/interview-prep"><img src="https://agentmods.dev/badge/commands/madebytokens/resume-helper/interview-prep.svg" alt="Measured on agentmods" height="20"></a>
Per session 7 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,136 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00007 $0.01136
Opus 5 $0.00003 $0.00568
Sonnet 5 $0.00001 $0.00227
Haiku 4.5 $0.00001 $0.00114

Measured 7d ago against content hash 90739aa71c10, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

interview-prep scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

commands/interview-prep.md · 210 lines

How it starts

The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Interview Prep Command

Generate an interview preparation document based on a resume.

Usage

/resume-helper:interview-prep "path/to/resume.md"
/resume-helper:interview-prep  # Uses resume from last completed loop

Instructions

Step 1: Load Resume

  1. If path provided, read the resume file
  2. If no path provided:
    • Read working/state.json
    • If state exists and has completed, read working/writer/output.md
    • If no state or no resume, ask user for resume path

Step 2: Analyze Resume

Invoke the Interviewer agent to generate likely interview questions:

You are the Interviewer agent. Analyze this resume and generate comprehensive interview questions.

## Resume
<resume content>

## Task
Generate interview questions that a hiring manager would likely ask based on this resume. For each claim or achievement, create questions that would verify or explore it deeper.

Organize questions by category:
1. Experience verification questions
2. Technical deep-dive questions
3. Behavioral/situational questions
4. Questions about gaps or transitions
5. Questions the candidate should ask the interviewer

Step 3: Generate Prep Document

Create working/output/interview_prep.md with the following structure:

# Interview Preparation Guide

Generated: [date]
Resume: [filename]

## Quick Reference

### Your Key Talking Points
- [Top 3-5 achievements to emphasize]

### Numbers to Remember
| Metric | Value | Context |
|--------|-------|---------|
| Team size | X | Project Y |
| Impact | X% | Achievement Z |
| ... | ... | ... |

## Likely Questions & Suggested Responses

### Experience Verification

**Q: [Question about specific role/achievement]**

*Why they're asking:* [What they want to verify]

*Suggested response framework:*
- Situation: [Context to set]
- Your role: [Clarify your specific contribution]
- Actions: [What you did]
- Result: [Quantified outcome]

*Key points to hit:*
- [Specific detail 1]
- [Specific detail 2]

---

### Technical Deep-Dives

**Q: [Technical question based on resume]**

*Why they're asking:* [What they want to assess]

*Suggested approach:*
- [How to structure your answer]
- [Technical details to include]
- [What to avoid]

---

### Behavioral Questions

**Q: "Tell me about a time when..." [scenario from resume]**

*STAR Response:*
- **Situation:** [Set the scene]
- **Task:** [Your responsibility]
- **Action:** [What you did - be specific]
- **Result:** [Quantified outcome]

---

### Questions About Gaps/Transitions

**Q: [Question about career gap or transition]**

*Suggested response:*
- [Honest, positive framing]
- [What you learned/did during that time]
- [How it makes you stronger for this role]

---

## Red Flags to Address Proactively

If these come up, here's how to handle them:

1. **[Potential concern]**
   - Address by: [suggested approach]

2. **[Potential concern]**
   - Address by: [suggested approach]

---

## Questions YOU Should Ask

Demonstrate engagement and evaluate fit:

### About the Role
- "What does success look like in the first 90 days?"
- "What are the biggest challenges facing the team right now?"

### About the Team
- "How is the team structured?"
- "What's the collaboration style?"

### About Growth
- "What opportunities for growth exist?"
- "How do you support professional development?"

### About the Company
- "What's the company's biggest priority this year?"
- "How would you describe the culture?"

---

## Final Checklist

Before the interview:
- [ ] Review all numbers and metrics in your resume
- [ ] Practice STAR responses for top 3 achievements
- [ ] Prepare 3-5 questions to ask
- [ ] Research the company and interviewer
- [ ] Review the job description again
- [ ] Prepare your "Tell me about yourself" (2-min version)

---

*Good luck! Remember: The best interviews feel like conversations, not interrogations.*

Read the full file on GitHub · 210 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 210 lines · 7 tokens per session scan A 90739aa71c10

Subscribe to this mod's changes

interview-prep is a command published in the GitHub repository MadeByTokens/resume-helper (7 stars, last pushed 7mo ago), licensed MIT. It adds 7 tokens to every session and 1,136 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.