test-cycle

Generate, validate, and execute Python unit tests with pytest.

1|1|Updated Feb 28, 2026
One-click install
npx skills add https://github.com/jakubstuglik/hybrid-code-rag-mcp --skill test-cycle
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: test-cycle
Source: https://github.com/jakubstuglik/hybrid-code-rag-mcp/tree/main/.opencode/skills/test-cycle
Command: npx skills add https://github.com/jakubstuglik/hybrid-code-rag-mcp --skill test-cycle

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pytest, pytest-cov, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a structured, repeatable workflow for generating, validating, executing, and improving unit tests for Python code, enhancing software quality assurance.

Core Features & Use Cases

  • Test Generation: Automatically creates comprehensive pytest test files for modules based on code analysis.
  • Validation & Review: Ensures test correctness, coverage, and adherence to project conventions before execution.
  • Iterative Improvement: Facilitates quick re-generation and rerunning of tests after fixes, supporting test-driven development and continuous integration.
  • Use Case: When a developer updates a core library, invoke this Skill to generate new tests, validate their quality, run them, and iterate until all tests pass, ensuring stable code.

Quick Start

Use the test cycle skill to automatically generate, validate, and run tests for your latest code changes, ensuring high-quality software delivery.

Frequently Asked Questions about test-cycle

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

FAQPage Schema
How do I automate Python unit test generation for code updates?

Automated Python unit test generation creates pytest test files by analyzing code updates, then validates, executes, and iterates on tests until they pass. This workflow supports continuous integration by ensuring code correctness and coverage throughout development.

Can I use pytest with continuous integration workflows for test-driven development?

Yes, pytest integrates with continuous integration workflows for test-driven development by automatically generating, reviewing, and executing test files. The iterative process re-generates and re-runs tests after fixes, ensuring all tests pass before code changes are merged.

What is the best way to validate pytest test coverage before execution?

Validating pytest test coverage before execution involves reviewing generated tests for correctness, coverage adequacy, and adherence to project conventions. This validation step ensures test quality and code correctness before tests are run in the development environment.

Do I need pytest and pytest-cov to run automated test generation workflows?

Yes, pytest and pytest-cov are required dependencies for this automated testing workflow. These Python testing tools verify code correctness and measure coverage during the generation, execution, and iteration steps of the unit test cycle.

How does iterative test improvement work for Python unit tests?

Iterative test improvement for Python unit tests works by re-generating and re-running pytest files after code fixes are applied. This cycle repeats until all tests pass, supporting stable code delivery through continuous validation and quality assurance.