monitoring-setup-guide

monitoring-setup-guide is a skill for Claude Code from cnfeat/top-pm-skills. It costs 124 tokens per session (5,239 once invoked), scanned A, original, MIT.

A monitoring setup guide explains what to measure in a service, how to collect logs and traces, and when alerts should fire. Observability means gathering enough information to understand what a running system is doing and why.

In plain words
What is it for?
Use it to plan metrics, logs, distributed tracing, dashboards, alert rules, business measurements, and observability work.
Why use it?
It gives teams a defined view of system health instead of leaving them unsure what is happening in production. It connects alerts and dashboards to real user journeys and operational questions.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the pm-engineering plugin — 37 skills shipped together

Good fit Use it to plan metrics, logs, distributed tracing, dashboards, alert rules, business measurements, and observability work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cnfeat/top-pm-skills/monitoring-setup-guide
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.

Any agent
npx skills add cnfeat/top-pm-skills --skill monitoring-setup-guide
Clone the repo
git clone --depth 1 https://github.com/cnfeat/top-pm-skills

Made for: Claude Code.

Or install pm-engineering, the plugin that ships this one along with the rest of its 37 skills.

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-setup-guide

README.md
[![agentmods](https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/monitoring-setup-guide.svg)](https://agentmods.dev/skills/cnfeat/top-pm-skills/monitoring-setup-guide)
Your own site
<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/monitoring-setup-guide"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/monitoring-setup-guide.svg" alt="Measured on agentmods" height="20"></a>
Per session 124 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,239 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00124 $0.05239
Opus 5 $0.00062 $0.02619
Sonnet 5 $0.00025 $0.01048
Haiku 4.5 $0.00012 $0.00524

Measured 4d ago against content hash fdc7b8b11d50, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

monitoring-setup-guide 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 4d 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.

参考skill/pm-claude-skills-main/pm-claude-skills-main/plugins/pm-engineering/skills/monitoring-setup-guide/SKILL.md · 445 lines

How it starts

The opening of the file, as written. The whole thing — 445 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Monitoring Setup Guide Skill

Produce a complete monitoring setup guide for a service — defining exactly what to measure, how to structure logs, how to configure alerts with actionable thresholds, and how to build dashboards that answer real operational questions. A good monitoring guide eliminates "we don't know what's happening in production" as a root cause category, and gives on-call engineers a single source of truth for what healthy looks like.

Required Inputs

Ask for these if not already provided:

  • Service name and description — what the service does and its role in the system
  • Tech stack — language, framework, and infrastructure (e.g. Go/gRPC on Kubernetes, Python/FastAPI on ECS)
  • Current monitoring tooling — Datadog, Prometheus + Grafana, CloudWatch, New Relic, Honeycomb, or none yet
  • Key user journeys — the 2–4 most important things a user or consumer does with the service (these drive what to alert on)
  • Existing alerts — paste any existing alert configurations or describe what's currently monitored

Output Format


Monitoring Setup Guide: [Service Name]

Team: [Team name] | Tech lead: [Name] Stack: [Language/Framework] on [Infrastructure] Monitoring platform: [Datadog / Prometheus+Grafana / CloudWatch / etc.] Date: [Date] | Review cycle: Quarterly


1. Monitoring Philosophy

Good monitoring answers three questions:

  1. Is the service healthy right now? (alerting)
  2. Was it healthy in the past, and is it trending worse? (dashboards + SLO tracking)
  3. Why did something fail? (logs + traces)

This guide defines the answers for [Service Name]. Every alert must be actionable — if an on-call engineer cannot take a specific action in response to the alert, the alert should not exist.

Key user journeys monitored:

  • Journey 1: [e.g. "User submits a payment — POST /charges, receives confirmation"]
  • Journey 2: [e.g. "User views transaction history — GET /transactions"]
  • Journey 3: [e.g. "Subscription renewal job runs — background worker processes billing events"]

Read the full file on GitHub · 445 lines

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. 4d ago First seen · 445 lines · 124 tokens per session scan A fdc7b8b11d50

Subscribe to this mod's changes

monitoring-setup-guide is a skill published in the GitHub repository cnfeat/top-pm-skills (48 stars, last pushed 2mo ago), licensed MIT. It adds 124 tokens to every session and 5,239 once invoked, about $0.0006 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 2026-09-03.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens