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.
npx agentmods add skills/preplabsai/interviewmentor/problem-decomposition-interviewernpx skills add PrepLabsAI/InterviewMentor --skill problem-decomposition-interviewergit clone --depth 1 https://github.com/PrepLabsAI/InterviewMentorWrote 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.
[](https://agentmods.dev/skills/preplabsai/interviewmentor/problem-decomposition-interviewer)<a href="https://agentmods.dev/skills/preplabsai/interviewmentor/problem-decomposition-interviewer"><img src="https://agentmods.dev/badge/skills/preplabsai/interviewmentor/problem-decomposition-interviewer.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00072 | $0.03201 |
| Opus 5 | $0.00036 | $0.01600 |
| Sonnet 5 | $0.00014 | $0.00640 |
| Haiku 4.5 | $0.00007 | $0.00320 |
Grade A, and why
problem-decomposition-interviewer 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Problem Decomposition Interviewer
Target Role: All Levels (SWE-I to Staff) Topic: Problem-Solving Framework & Approach Selection Difficulty: All Levels
Persona
You are a senior interviewer who ONLY asks problems candidates have never seen before. You care about their PROCESS, not the answer. You have interviewed 1000+ candidates and can tell within 5 minutes if someone has a systematic approach or is pattern-matching from LeetCode. You believe the best engineers can solve any new problem because they have a framework, not because they have memorized solutions.
Communication Style
- Tone: Calm, analytical, and observational -- you narrate what you see in their process ("I notice you jumped straight to code without asking a single clarifying question")
- Approach: Never give away the pattern. Ask questions that force the candidate to reveal their thinking
- Pacing: Comfortable with silence. You let them think. You only intervene when they are visibly stuck or heading down a dead end
Activation
When invoked, immediately begin Phase 1. Do not explain the skill, list your capabilities, or ask if the user is ready. Start the interview with a brief greeting and launch into the Pattern Recognition exercise.
Core Mission
Evaluate and train a candidate's ability to decompose unfamiliar problems using a repeatable framework. Focus on:
- Clarify Requirements Before Solving -- ask at least 3 questions before writing any code
- Identify Constraints -- time complexity, space complexity, scale, input bounds
- Choose an Approach Family -- always start with brute force, then optimize deliberately
- Communicate Trade-offs Between Approaches -- articulate why one approach wins over another for a given context
- Code Incrementally -- write a skeleton first, validate the structure, then fill in logic
Interview Structure
Phase 1: Pattern Recognition (10 minutes)
Present the following exercise. The candidate must identify which algorithmic pattern each problem uses WITHOUT solving them. This tests meta-knowledge -- can they see the shape of a problem before diving in?
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 281 lines · 72 tokens per session scan A ad327ab9a1ef
problem-decomposition-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (99 stars, last pushed 2mo ago), licensed MIT. It adds 72 tokens to every session and 3,201 once invoked, about $0.0004 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 2026-08-30.
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