test-ops

Automate end-to-end Python testing workflows across CI/CD platforms.

1|Updated Dec 22, 2025
One-click install
npx skills add https://github.com/CybLow/pypaginate --skill test-ops
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: test-ops
Source: https://github.com/CybLow/pypaginate/tree/main/.opencode/skills/test-ops
Command: npx skills add https://github.com/CybLow/pypaginate --skill test-ops

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates end-to-end Python testing workflows across CI/CD platforms and ensures consistent quality across pipelines.

Core Features & Use Cases

  • GitHub Actions Workflow templates for automated linting, testing, and coverage reporting.
  • GitLab CI pipelines and multi-stage test strategies with parallelization.
  • Coverage reporting integration and configurable test strategies for unit, integration, and E2E tests.

Quick Start

Enable TestOps in your repository by following the provided YAML templates and running the CI workflow to validate tests.

Frequently Asked Questions about test-ops

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

FAQPage Schema
How do I automate Python testing workflows in GitHub Actions and GitLab CI?

Automating Python testing in GitHub Actions and GitLab CI involves configuring YAML templates for linting, unit, integration, and e2e tests with stage-based gating. This standardizes test commands and ensures consistent quality across multi-stage pipelines.

How do I run parallel pytest tests in a CI/CD pipeline?

Running parallel pytest tests in a CI/CD pipeline leverages pytest-xdist to distribute tests across multiple workers. This reduces execution time and provides faster feedback during multi-stage test strategies with coverage reporting.

What is the best way to configure UV tooling for a Python testing strategy?

Configuring UV tooling for a Python testing strategy standardizes test commands and manages dependencies efficiently. It integrates with multi-stage pipelines to enable production-grade linting, testing, and coverage reporting.

Does this approach support multi-stage test strategies with gating?

Yes, multi-stage test strategies support stage-based gating by separating linting, unit, integration, and e2e tests into distinct pipeline phases. This ensures code quality checks pass before progressing to subsequent stages.

How do I generate coverage reports in automated Python CI pipelines?

Generating coverage reports in automated Python CI pipelines integrates pytest coverage tools within GitHub Actions or GitLab CI workflows. This automatically collects and reports code coverage metrics during testing.