prometheus-monitoring
Set up Prometheus monitoring for applications with custom metrics, scraping configurations, and service discovery. Use when implementing time-series metrics collection, monitoring applications, or building observability infrastructure.
- Installs
- 510
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill prometheus-monitoring- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads prometheus-monitoring automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Prometheus Monitoring
Table of Contents
Overview
Implement comprehensive Prometheus monitoring infrastructure for collecting, storing, and querying time-series metrics from applications and infrastructure.
When to Use
- Setting up metrics collection
- Creating custom application metrics
- Configuring scraping targets
- Implementing service discovery
- Building monitoring infrastructure
Quick Start
Minimal working example:
# /etc/prometheus/prometheus.yml
global:
scrape_interval: 15s
evaluation_interval: 15s
external_labels:
cluster: production
alerting:
alertmanagers:
- static_configs:
- targets: ["localhost:9093"]
rule_files:
- "/etc/prometheus/alert_rules.yml"
scrape_configs:
- job_name: "prometheus"
static_configs:
- targets: ["localhost:9090"]
- job_name: "node"
static_configs:
- targets: ["localhost:9100"]
- job_name: "api-service"
// ... (see reference guides for full implementation)
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| Prometheus Configuration | Prometheus Configuration |
| Node.js Metrics Implementation | Node.js Metrics Implementation |
| Python Prometheus Integration | Python Prometheus Integration |
| Alert Rules | Alert Rules |
| Docker Compose Setup | Docker Compose Setup |
Best Practices
✅ DO
- Use consistent metric naming conventions
- Add comprehensive labels for filtering
- Set appropriate scrape intervals (10-60s)
- Implement retention policies
- Monitor Prometheus itself
- Test alert rules before deployment
- Document metric meanings
❌ DON'T
- Add unbounded cardinality labels
- Scrape too frequently (< 10s)
- Ignore metric naming conventions
- Create alerts without runbooks
- Store raw event data in Prometheus
- Use counters for gauge-like values
FAQ
What does the prometheus-monitoring skill do?
Set up Prometheus monitoring for applications with custom metrics, scraping configurations, and service discovery. Use when implementing time-series metrics collection, monitoring applications, or building observability infrastructure.
How do I install prometheus-monitoring?
Run npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill prometheus-monitoring in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/prometheus-monitoring/ (personal) or .claude/skills/prometheus-monitoring/ (project).
Which AI agents can use prometheus-monitoring?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is prometheus-monitoring safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains prometheus-monitoring?
It is published by aj-geddes in aj-geddes/useful-ai-prompts. It has 510 recorded installs.
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