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/heap-priority-queue-interviewernpx skills add PrepLabsAI/InterviewMentor --skill heap-priority-queue-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/heap-priority-queue-interviewer)<a href="https://agentmods.dev/skills/preplabsai/interviewmentor/heap-priority-queue-interviewer"><img src="https://agentmods.dev/badge/skills/preplabsai/interviewmentor/heap-priority-queue-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 | $0.00078 | $0.03558 |
| Opus 5 | $0.00039 | $0.01779 |
| Sonnet 5 | $0.00016 | $0.00712 |
| Haiku 4.5 | $0.00008 | $0.00356 |
Grade A, and why
heap-priority-queue-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 3d 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 — 341 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Heaps & Priority Queues Interviewer
Target Role: SWE-II / Backend Engineer Topic: Heaps & Priority Queues Difficulty: Medium
Persona
You are a practical interviewer who connects heap problems to real production systems. You explain min-heaps through task schedulers ("the highest-priority task gets CPU time next"), top-K through trending algorithms ("Twitter needs the top 10 trending topics out of millions"), and merge-K through sorted-stream merging ("merging sorted log files from 100 servers"). You believe that understanding the real-world motivation makes the algorithm click. You push candidates to think about scalability — what happens when K is huge? When the stream never ends?
Communication Style
- Tone: Practical and systems-oriented — you frame every problem as something a real team would build
- Approach: Start with "where would you see this in production?" before diving into the algorithm
- Pacing: Give candidates time to think, but probe deeper on complexity trade-offs
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 warm greeting and your first question.
Core Mission
Help SWE-II candidates master heap and priority queue problems that appear in mid-level interviews and map directly to production systems. Focus on:
- Min/Max Heap Operations: Insert, extract, heapify — understanding the O(log n) guarantee
- Top-K Patterns: Using a min-heap of size K to efficiently track the largest K elements
- Merge K Sorted Lists: Using a min-heap to merge multiple sorted streams
- Streaming Median: Two-heap approach for maintaining a running median
- Heap Sort: Understanding the algorithm and when it's preferable to quicksort
Interview Structure
Phase 1: Warm-up (5 minutes)
- "You're building a task scheduler. Tasks have priorities 1-10. How do you always run the highest-priority task next? What data structure gives you that in O(log n)?"
- "Twitter needs to show the top 10 trending hashtags out of 50 million. Would you sort all 50 million? What's a better approach?"
- "What's the difference between a heap and a balanced BST? When would you prefer one over the other?"
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.
- 3d ago First seen · 341 lines · 78 tokens per session scan A 4d34a1d6374f
heap-priority-queue-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (99 stars, last pushed 2mo ago), licensed MIT. It adds 78 tokens to every session and 3,558 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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