List Regressions

Fetch and filter OpenShift component regression data across releases.

112|305|Updated Oct 10, 2025

Search Tags:#regression #openshift #release-analysis #quality-metrics #component-health

Ready to run

npx skills add https://github.com/openshift-eng/ai-helpers --skill list-regressions

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: List Regressions
Source: https://github.com/openshift-eng/ai-helpers/tree/main/plugins/component-health/skills/list-regressions
Command: npx skills add https://github.com/openshift-eng/ai-helpers --skill list-regressions

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill eliminates manual data gathering and analysis of OpenShift component regressions, providing instant insights into release quality and stability.

Core Features & Use Cases

Regression Analysis: Fetch and analyze regression data across OpenShift releases with detailed metrics.
Component Filtering: Focus analysis on specific components like Monitoring, etcd, or kube-apiserver.
Use Case: Imagine you need to assess the health of OpenShift 4.21 release. Use this Skill to get comprehensive regression statistics for the Monitoring component, including triage rates and time-to-resolution metrics.

Quick Start

Use the List Regressions skill to fetch all regressions for OpenShift release 4.17 and analyze the component health trends.

Frequently Asked Questions about List Regressions

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

FAQPage Schema

How do I analyze OpenShift component regressions across releases?▼

Regression analysis for OpenShift components fetches and structures data by release, component, and development window. This Skill queries regression metrics including triage rates and time-to-resolution, filtering results to focus on specific components like Monitoring, etcd, or kube-apiserver for targeted health assessment.

Can I filter regression data by specific OpenShift components and releases?▼

Yes. The Skill filters regression data by release version, optional component names, and development window, producing component-scoped results. This lets you isolate health trends for particular components across multiple OpenShift releases in a single structured view.

What are the requirements to fetch and process OpenShift regression data?▼

Requirements include Python 3.6 or higher, network access to fetch regression data, and an updated API endpoint configured in list_regressions.py. The Skill uses only the Python standard library, eliminating external dependencies for data fetching and processing.

How do I assess OpenShift release quality using regression metrics?▼

Regression analysis provides instant insights into release quality and stability by gathering regression statistics automatically. Fetch regressions for a target release, examine component-level metrics like triage rates and resolution times, then compare trends across versions to identify stability patterns.

What data does the Skill produce for component health monitoring?▼

The Skill produces structured, component-scoped regression data including triage rates, time-to-resolution metrics, and release-specific statistics. This output is formatted for direct analysis of component health trends without manual data gathering.