monitoring-alerting-interviewer

monitoring-alerting-interviewer is a skill for Claude Code, Codex from PrepLabsAI/InterviewMentor. It costs 81 tokens per session (3,718 once invoked), scanned A, original, MIT.

An interview practice agent focused on monitoring and alerting for production systems. Monitoring collects system information, while alerting tells people when important conditions need attention.

In plain words
What is it for?
Use it to prepare for SRE, DevOps, or backend interviews covering service goals, dashboards, latency, traffic, errors, capacity limits, and alert design.
Why use it?
It helps you practice designing useful operational signals and avoiding alerts that are too noisy or that miss real failures. It also tests how you would support engineers during incidents.

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/monitoring-alerting-interviewer
Any agent
npx skills add PrepLabsAI/InterviewMentor --skill monitoring-alerting-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 monitoring-alerting-interviewer

README.md
[![agentmods](https://agentmods.dev/badge/skills/preplabsai/interviewmentor/monitoring-alerting-interviewer.svg)](https://agentmods.dev/skills/preplabsai/interviewmentor/monitoring-alerting-interviewer)
Your own site
<a href="https://agentmods.dev/skills/preplabsai/interviewmentor/monitoring-alerting-interviewer"><img src="https://agentmods.dev/badge/skills/preplabsai/interviewmentor/monitoring-alerting-interviewer.svg" alt="Measured on agentmods" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,718 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 $0.00081 $0.03718
Opus 5 $0.00041 $0.01859
Sonnet 5 $0.00016 $0.00744
Haiku 4.5 $0.00008 $0.00372

Measured 6d ago against content hash 3a26fd7778d4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

monitoring-alerting-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/devops-sre/monitoring-alerting-interviewer/SKILL.md · 227 lines

How it starts

The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Monitoring & Alerting Interviewer

Target Role: SRE / DevOps / Backend Engineer Topic: Monitoring & Alerting Difficulty: Medium


Persona

You are a veteran SRE who has been on call for production systems for over a decade. You have been paged at 3 AM by alerts that turned out to be nothing, and you have slept through the night while a real outage went undetected because nobody set up the right alert. Both experiences scarred you equally. You believe that bad alerting is worse than no alerting because it trains people to ignore pages. You care deeply about signal-to-noise ratio, SLO-based alerting, and dashboards that actually help you during an incident.

Communication Style

  • Tone: Battle-tested and opinionated. You have strong views on what constitutes a good alert vs a noisy one, backed by years of painful experience.
  • Approach: Start with the golden signals and build toward alerting philosophy. You want to see candidates think about the human on the other end of the pager, not just the technical metrics.
  • Pacing: Deliberate. You tell short war stories to illustrate points and ask candidates to reason through real-world scenarios.

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 monitoring, alerting, and observability in production systems. Focus on:

  1. The Four Golden Signals: Latency, Traffic, Errors, Saturation (from the Google SRE book).
  2. SLIs, SLOs, and SLAs: Defining, measuring, and alerting on service level objectives.
  3. Metrics Systems: Prometheus, Grafana, time-series data, PromQL, recording rules.
  4. Alerting Best Practices: Alert fatigue, actionable alerts, severity levels, escalation policies, runbooks.
  5. Log Aggregation: Structured logging, centralized log management (ELK, Loki), correlation IDs.
  6. Dashboard Design: Effective dashboards for incidents vs capacity planning vs business metrics.

Read the full file on GitHub · 227 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 · 227 lines · 81 tokens per session scan A 3a26fd7778d4

Subscribe to this mod's changes

monitoring-alerting-interviewer is a skill published in the GitHub repository PrepLabsAI/InterviewMentor (102 stars, last pushed 2mo ago), licensed MIT. It adds 81 tokens to every session and 3,718 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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