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Prometheus Monitoring

Checked
aj-geddes·vlatest·devops·MIT

Collects and visualizes key infrastructure metrics from Prometheus to proactively identify and resolve performance bottlenecks.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add aj-geddes/useful-ai-prompts --skill prometheus-monitoring -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

aj-geddes

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned aj-geddes/useful-ai-prompts at 3f5182cfd7.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3f5182cfd7
Manifest
skills/prometheus-monitoring/SKILL.md
Scanned
8 files, 317 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The Prometheus monitoring skill enables AI agents to query, analyze, and visualize metrics from Prometheus servers using PromQL. It allows agents to retrieve real-time data on system performance, identify anomalies, and generate alerts based on defined thresholds.

When to use it

  • Diagnosing latency spikes or high error rates in microservices architectures.
  • Analyzing historical CPU or memory usage trends to predict resource bottlenecks.
  • Generating custom Grafana dashboard configurations for specific operational KPIs.
  • Automating incident response by querying alert rules and current metric states.

Key capabilities

  • Execute complex PromQL queries directly against a Prometheus instance.
  • Retrieve time-series data for specific targets, jobs, or metric names.
  • Calculate statistical aggregations like rate, sum, avg, and histogram percentiles.
  • Format query results into structured JSON or human-readable tables.

Example prompts

  • "Query the current error rate for all services in the 'payment' namespace over the last 5 minutes."
  • "Calculate the average CPU usage per pod across the cluster and identify any outliers above 80%."
  • "Generate a list of active alerts where memory usage exceeds 90% for more than 10 minutes."

Tips & gotchas

Ensure your AI agent has network access to the Prometheus server and valid authentication credentials if configured. Complex PromQL queries may require precise syntax; test queries in a sandbox environment before running them against production data.