pytest-runner

Executes Python test suites with pytest and generates detailed coverage reports.

14|2|Updated Jan 28, 2026

Search Tags:#testing #test automation #debugging #pytest #code coverage #python

Ready to run

npx skills add https://github.com/excatt/superclaude-plusplus --skill pytest-runner-excatt

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pytest-runner
Source: https://github.com/excatt/superclaude-plusplus/tree/main/skills/pytest-runner
Command: npx skills add https://github.com/excatt/superclaude-plusplus --skill pytest-runner-excatt

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the execution, analysis, and debugging of Python test suites, ensuring code quality and identifying issues efficiently.

Core Features & Use Cases

Automated Test Execution: Runs tests using pytest, with options for quick runs, full coverage, or re-running only failed tests.
Coverage Analysis: Generates detailed coverage reports, highlighting uncovered lines and suggesting tests.
Failure Diagnosis: Provides clear output for failed tests, including expected vs. actual results and suggested fixes.
Fixture Insights: Analyzes fixture dependencies and identifies slow fixtures for optimization.
Use Case: After writing new Python code, use this Skill to automatically run all associated tests, check code coverage, and get a clear report of any failures or areas needing more tests.

Quick Start

Run all Python tests and generate a coverage report.

Frequently Asked Questions about pytest-runner

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

FAQPage Schema

How do I run Python tests and generate a code coverage report?▼

To run Python tests and generate a code coverage report, execute your test suite using pytest with coverage options enabled. This Skill automates the execution, analyzes the results, and highlights uncovered lines to ensure code quality and identify regressions.

What is the best way to debug failing pytest fixtures?▼

The best way to debug failing pytest fixtures is to analyze fixture dependencies and identify slow fixtures for optimization. This Skill provides fixture insights and failure diagnosis, comparing expected versus actual results to suggest fixes for your Python tests.

Can I integrate pytest execution with CI/CD pipelines and pre-commit hooks?▼

Yes, you can integrate pytest execution with CI/CD pipelines and pre-commit hooks for automated testing workflows. This allows you to automatically run Python test suites, check code coverage, and block commits if failures or regressions are detected.

How do I re-run only failed Python tests after a full test suite execution?▼

To re-run only failed Python tests after a full suite execution, use the targeted re-run option provided by this pytest automation Skill. This quickly isolates and executes previously failed tests, providing clear output for failure diagnosis and suggested fixes.

Does automated pytest analysis help identify slow Python test fixtures?▼

Yes, automated pytest analysis helps identify slow Python test fixtures by evaluating fixture dependencies during test execution. This process pinpoints performance bottlenecks within your test suite, allowing you to optimize test automation workflows and improve overall execution speed.

Why does my Python test suite report low code coverage and how do I find untested lines?▼

Your Python test suite reports low code coverage because certain code paths lack associated tests. This Skill generates detailed coverage reports using pytest, highlighting uncovered lines and suggesting specific tests to improve overall code quality and identify regressions.