prometheus-configuration
Helps your agent set up a system to collect and monitor important metrics. It's useful for ensuring infrastructure and applications are running smoothly.
What it does
This tool helps you set up Prometheus, a system for collecting and monitoring performance data from your infrastructure and applications. It ensures you can see what's happening and get alerted if something goes wrong.
When to use it
- ✓When you need to start monitoring your systems.
- ✓When configuring how to collect performance data.
- ✓To create rules that warn about problems.
Example of what to ask your AI
“Set up Prometheus to collect metrics from my web servers.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
You provide information about what data to collect and how to collect it. The tool organizes these settings so Prometheus can start monitoring your systems automatically.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add wshobson/agents --skill prometheus-configurationOr download just the file:
curl -L https://raw.githubusercontent.com/wshobson/agents/main/plugins/observability-monitoring/skills/prometheus-configuration/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Prometheus Configuration
Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.
Purpose
Configure Prometheus for comprehensive metric collection, alerting, and monitoring of infrastructure and applications.
When to Use
- Set up Prometheus monitoring
- Configure metric scraping
- Create recording rules
- Design alert rules
- Implement service discovery
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Best Practices
- Use consistent naming for metrics (prefix_name_unit)
- Set appropriate scrape intervals (15-60s typical)
- Use recording rules for expensive queries
- Implement high availability (multiple Prometheus instances)
- Configure retention based on storage capacity
- Use relabeling for metric cleanup
- Monitor Prometheus itself
- Implement federation for large deployments
- Use Thanos/Cortex for long-term storage
- Document custom metrics
Troubleshooting
Check scrape targets:
curl http://localhost:9090/api/v1/targets
Check configuration:
curl http://localhost:9090/api/v1/status/config
Test query:
curl 'http://localhost:9090/api/v1/query?query=up'
Related Skills
grafana-dashboards- For visualizationslo-implementation- For SLO monitoringdistributed-tracing- For request tracing
FAQ
What are 'metrics'?
Metrics are like vital signs for your systems. They measure things like CPU usage, memory, or the number of requests a server is receiving.
What is 'scraping'?
Scraping is the process where Prometheus goes to your systems and 'collects' the metrics they are reporting.
What are 'recording rules' and 'alerting rules'?
Recording rules help pre-calculate metrics that are used frequently. Alerting rules define conditions that, when met, trigger a warning.
Details
Original description by the author
Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
repo: wshobson/agents
Popularity
- GitHub stars
- 41k
- Ranking position
- #4909
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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