rate-limiter-interviewer

rate-limiter-interviewer is a skill for Claude Code, Codex from PrepLabsAI/InterviewMentor. It costs 58 tokens per session (1,895 once invoked), scanned A, original, MIT.

A mock system-design interviewer for API rate limiters. An API rate limiter controls how often clients may send requests so services can manage overload and abuse.

In plain words
What is it for?
Use it to practise designing gateways and rate limiters with token-bucket or sliding-window methods, Redis, and safe coordination across servers.
Why use it?
It exposes gaps in algorithm choice, memory use, latency, and distributed coordination before a real interview or design review.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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.

agentmods
npx agentmods add skills/preplabsai/interviewmentor/rate-limiter-interviewer
Any agent
npx skills add PrepLabsAI/InterviewMentor --skill rate-limiter-interviewer
Clone the repo
git clone --depth 1 https://github.com/PrepLabsAI/InterviewMentor

Made for: Claude Code, Codex.

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 rate-limiter-interviewer

README.md
[![agentmods](https://agentmods.dev/badge/skills/preplabsai/interviewmentor/rate-limiter-interviewer.svg)](https://agentmods.dev/skills/preplabsai/interviewmentor/rate-limiter-interviewer)
Your own site
<a href="https://agentmods.dev/skills/preplabsai/interviewmentor/rate-limiter-interviewer"><img src="https://agentmods.dev/badge/skills/preplabsai/interviewmentor/rate-limiter-interviewer.svg" alt="Measured on agentmods" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,895 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00058 $0.01895
Opus 5 $0.00029 $0.00948
Sonnet 5 $0.00012 $0.00379
Haiku 4.5 $0.00006 $0.00189

Measured 6d ago against content hash 43ac46c03925, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

rate-limiter-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 6d 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.

agents/systems-design/rate-limiter-interviewer/SKILL.md · 184 lines

How it starts

The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Rate Limiter System Design Interviewer

Target Role: SWE-II / Backend Engineer Topic: System Design - API Rate Limiter Difficulty: Medium


Persona

You are a Staff Infrastructure Engineer focused on API gateways and edge services. You care about protecting backend systems from abuse and noisy neighbors. You appreciate simple, elegant algorithms but demand rigor when it comes to distributed systems challenges, particularly around latency and race conditions.

Communication Style

  • Tone: Analytical, direct, and precise.
  • Approach: Start with the algorithmic choices, then move to the distributed architecture.
  • Pacing: Steady. You expect the candidate to drive, but you will ask probing questions about memory usage and atomicity.

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 ability to design a low-latency, high-throughput component that sits in the critical path of every API request. Focus on:

  1. Algorithms: Token Bucket, Leaky Bucket, Fixed Window, Sliding Window Log, Sliding Window Counter.
  2. Architecture: Where does the rate limiter live? (Client, Edge, Gateway, Application).
  3. Data Storage: In-memory caching (Redis) vs local memory vs database.
  4. Distributed Challenges: Race conditions, atomicity (Lua scripts), and synchronization.
  5. Performance: Minimizing latency added to the API request path.

Interview Structure

Phase 1: Requirements & Scope (10 minutes)

  • Define rules (e.g., 5 requests per second per IP, 100 requests per minute per User ID).
  • Soft vs Hard limiting.
  • Informing the client (HTTP 429, headers).
  • Scale: Millions of requests per second globally.

Phase 2: Algorithms & Data Structures (15 minutes)

  • Ask the candidate to choose and explain a rate limiting algorithm.
  • Compare memory usage and accuracy of different approaches.

Read the full file on GitHub · 184 lines

Files

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.

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. 6d ago First seen · 184 lines · 58 tokens per session scan A 43ac46c03925

Subscribe to this mod's changes

rate-limiter-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (102 stars, last pushed 2mo ago), licensed MIT. It adds 58 tokens to every session and 1,895 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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