promql

Write, interpret, and optimize PromQL queries for Prometheus metrics analysis.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/tylertitsworth/skills --skill promql
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: promql
Source: https://github.com/tylertitsworth/skills/tree/main/promql
Command: npx skills add https://github.com/tylertitsworth/skills --skill promql

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

PromQL query writing, interpretation, and optimization enable effective Prometheus metrics analysis.

Core Features & Use Cases

  • Instant and range vector queries to retrieve time-series data.
  • Advanced operators, aggregations, and functions for dashboards and alerts.
  • Pattern-based joins and label manipulation (label_replace, label_join) to correlate metrics across sources.
  • Real-world use: troubleshoot alerts by examining rate and percentile metrics across namespaces.

Quick Start

Try evaluating a simple rate over a 5-minute window in Prometheus to observe per-second request rates.

Frequently Asked Questions about promql

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a PromQL query to calculate per-second request rates?

To calculate per-second request rates in PromQL, apply the rate function over a range vector, such as evaluating a 5-minute window. This retrieves time-series data to observe per-second request rates for effective Prometheus metrics analysis.

What's the best way to troubleshoot Prometheus alerts across Kubernetes namespaces?

Troubleshooting Prometheus alerts across Kubernetes namespaces involves examining rate and percentile metrics using PromQL. You can apply instant and range vector selectors with aggregations to isolate workload anomalies and interpret alert behavior.

Can I use label_replace and label_join to correlate Prometheus metrics from different sources?

Yes, you can use label_replace and label_join in PromQL to manipulate labels and perform pattern-based joins. This correlates metrics across different sources for unified dashboard visualization and alert rule optimization.

How do instant and range vectors work when retrieving Prometheus time-series data?

Instant vectors retrieve current values for a set of time series, while range vectors fetch data points over a specified time duration in PromQL. Both are foundational for applying advanced operators, aggregations, and functions.

Does PromQL support arithmetic and aggregations for building cloud-native dashboards?

PromQL supports arithmetic operations, aggregations, and functions specifically designed for building cloud-native dashboards. These features enable effective query writing and optimization for analyzing Kubernetes and cloud-native workloads.