python-testing

Generate pytest tests for AI-authored Python code with coverage checks.

5|3|Updated Jun 18, 2024
One-click install
npx skills add https://github.com/Unique-AG/ai --skill python-testing-unique-ag
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-testing
Source: https://github.com/Unique-AG/ai/tree/main/.claude/skills/python-testing
Command: npx skills add https://github.com/Unique-AG/ai --skill python-testing-unique-ag

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and assets (resource) components.

What problem does it solve?

Write and maintain focused, deterministic pytest tests for AI-authored Python code, reducing debugging time and ensuring reliability.

Core Features & Use Cases

  • Test generation: Create well-documented tests that follow project conventions.
  • Coverage checks: Identify untested lines per file or folder to improve test quality.
  • Bootstrap setup: Install dev dependencies and apply recommended pytest configuration for new projects.

Quick Start

Use this skill to generate focused pytest tests for a module following the conventions described in this skill.

Frequently Asked Questions about python-testing

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

FAQPage Schema
How do I generate pytest tests for AI-authored Python code?▼

Generate pytest tests for AI-authored Python code by automating the creation of focused, deterministic test suites. This skill produces well-documented tests that conform to project conventions for test naming, docstrings, fixtures, and mocking.

What is the best way to check pytest coverage for untested Python modules?▼

Checking pytest coverage identifies untested lines per file or folder to improve test quality. This skill evaluates coverage targets across modules and features in a codebase, highlighting gaps in AI-authored Python code.

Can I bootstrap pytest configuration and dev dependencies for a new Python project?▼

You can bootstrap pytest configuration by installing dev dependencies and applying recommended settings for new projects. This skill provides the setup needed to establish a deterministic testing environment from scratch.

Does this test generation approach handle mocking and fixtures automatically?▼

Test generation handles mocking and fixtures automatically by conforming to established conventions. This ensures the generated pytest tests remain deterministic, well-documented, and safe from import issues across different modules.

Why should I use deterministic pytest tests for AI-generated code?▼

Deterministic pytest tests reduce debugging time and ensure the reliability of AI-authored Python code. They provide focused, well-documented validation that follows project conventions, preventing flaky test behavior.

When do I need to regenerate pytest tests for existing Python modules?▼

You need to regenerate pytest tests when adding new features or when coverage checks reveal untested lines in existing modules. This ensures AI-authored code maintains reliability and conforms to updated project conventions.