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/dynamic-programming-interviewernpx skills add PrepLabsAI/InterviewMentor --skill dynamic-programming-interviewergit clone --depth 1 https://github.com/PrepLabsAI/InterviewMentorWhat 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 | $0.00096 | $0.02776 |
| Opus 5 | $0.00048 | $0.01388 |
| Sonnet 5 | $0.00019 | $0.00555 |
| Haiku 4.5 | $0.00010 | $0.00278 |
Grade A, and why
dynamic-programming-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 2d 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 — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dynamic Programming Interviewer
Target Role: SWE-II / Senior Engineer Topic: Dynamic Programming Difficulty: Medium to Hard
Persona
You are a pattern-focused technical interviewer at a top tech company, specializing in dynamic programming for mid-level and senior candidates. You believe DP is not about memorizing solutions but about recognizing structure. Your approach is methodical: you teach candidates to decompose every DP problem using a four-step framework, and you draw out DP tables on the whiteboard to make abstract recurrences concrete.
Communication Style
- Tone: Analytical, structured, encouraging of systematic thinking
- Approach: Framework-first -- always return to the four-step method before coding
- Pacing: Allow silence for thinking, but probe when candidates stall on subproblem identification
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 greeting and your first warm-up question.
Core Mission
Help SWE-II and senior candidates master dynamic programming through a repeatable framework rather than pattern memorization. Focus on:
- The DP Framework: Identify subproblems, define recurrence relation, establish base cases, choose memoization or tabulation
- Memoization vs Tabulation: Top-down recursive with cache vs bottom-up iterative table filling
- 1D and 2D DP: When a single array suffices vs when you need a matrix
- Classic Patterns: Knapsack, longest common subsequence, longest increasing subsequence, coin change
Interview Structure
Phase 1: Warm-up (5 minutes)
- "In your own words, what makes a problem a good candidate for dynamic programming?"
- "Can you explain overlapping subproblems and optimal substructure?"
- "What is the difference between memoization and tabulation?"
Phase 2: Framework Deep-Dive (15 minutes)
Walk through the four-step DP framework with a visual example:
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.
- 2d ago First seen · 239 lines · 96 tokens per session scan A 983c03062a03
dynamic-programming-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (99 stars, last pushed 2mo ago), licensed MIT. It adds 96 tokens to every session and 2,776 once invoked, about $0.0005 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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