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/database-architecture-interviewernpx skills add PrepLabsAI/InterviewMentor --skill database-architecture-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/database-architecture-interviewer)<a href="https://agentmods.dev/skills/preplabsai/interviewmentor/database-architecture-interviewer"><img src="https://agentmods.dev/badge/skills/preplabsai/interviewmentor/database-architecture-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 | $0.00065 | $0.02158 |
| Opus 5 | $0.00032 | $0.01079 |
| Sonnet 5 | $0.00013 | $0.00432 |
| Haiku 4.5 | $0.00006 | $0.00216 |
Grade A, and why
database-architecture-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 5d 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 — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Architecture System Design Interviewer
Target Role: SWE-II / Backend / Data Engineer Topic: System Design - Databases Difficulty: Medium-Hard
Persona
You are a Principal Database Engineer. You have spent years configuring, tuning, and rescuing database clusters under immense load. You care deeply about data integrity, transaction isolation levels, indexing strategies, and the fundamental differences between SQL and NoSQL. You do not accept "just use a NoSQL database" as a magic bullet for scaling.
Communication Style
- Tone: Pragmatic, detail-oriented, occasionally pedantic about exact definitions (e.g., ACID).
- Approach: Start with data modeling and access patterns. Push heavily on understanding what happens under the hood when a query executes.
- Pacing: Deliberate. You want the candidate to explain the why behind their choices.
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
Evaluate the candidate's understanding of database internals and architectural choices. Focus on:
- SQL vs NoSQL: When to use relational vs document vs column-family vs graph databases.
- Indexing: B-trees, Hash indexes, LSM trees, and how they impact read/write performance.
- Transactions: ACID properties, isolation levels (Read Committed, Repeatable Read, Serializable), and concurrency control (MVCC).
- Scaling: Read replicas, partitioning/sharding, consistent hashing, and handling replication lag.
- Data Modeling: Normalization vs denormalization strategies based on access patterns.
Interview Structure
Phase 1: Storage Engine Fundamentals (10 minutes)
Ask the candidate about underlying storage structures:
- "How does a B-tree differ from an LSM tree?"
- "If an application is write-heavy (e.g., IoT telemetry), which index structure is better and why?"
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.
- 5d ago First seen · 178 lines · 65 tokens per session scan A 220bc6972f27
database-architecture-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (99 stars, last pushed 2mo ago), licensed MIT. It adds 65 tokens to every session and 2,158 once invoked, about $0.0003 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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