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python-mutation-test

Inject synthetic bugs into Python source code to measure test suite detection.

1|Updated Jun 20, 2026
Search Tags:#pytest#python#quality-assurance#test-coverage#mutation-testing#regression-testing
One-click install
npx skills add https://github.com/shafibabar/SDLC-Artifact-Factory --skill python-mutation-test
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: python-mutation-test
Source: https://github.com/shafibabar/SDLC-Artifact-Factory/tree/main/skills/python-mutation-test
Command: npx skills add https://github.com/shafibabar/SDLC-Artifact-Factory --skill python-mutation-test

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill addresses the gap between high line coverage and actual test effectiveness by identifying weak assertions that fail to detect bugs in production logic.

Core Features & Use Cases

  • Mutation Analysis: Injects syntactically valid bugs into source code to verify if the test suite catches them.
  • Triage Workflow: Provides a structured process to distinguish between real testing gaps and equivalent mutants.
  • Use Case: Use this skill to periodically gate the quality of domain and service layer packages, ensuring that critical business logic is protected against regressions that standard coverage metrics miss.

Quick Start

Run the python mutation test skill to analyze the domain and service layer packages and generate a report of survived mutants for triage.

Frequently Asked Questions about python-mutation-test

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

FAQPage Schema
How does mutation testing find weak assertions that high test coverage misses?▼

Yes, you can use mutation testing to gate domain and service layer packages. By injecting bugs and measuring detection rates, it enforces a minimum mutation score threshold to ensure high-quality regression protection for critical logic.

What is the best way to run mutation analysis with pytest?▼

The best way to run mutation analysis with pytest is to target domain and service layer packages, executing mutmut to inject bugs and generate a report of survived mutants for structured triage.

Do I need mutmut to perform Python mutation testing?▼

No, you do not need to manually fix every survived mutant. A triage workflow provides a structured process to distinguish real testing gaps requiring new assertions from equivalent mutants that do not need fixing.

When should I not use mutation testing for Python code?▼

You should not use mutation testing for non-business-critical code. It targets domain and service layer packages to ensure regression protection, and equivalent mutants can create triage overhead for logic that does not require high-quality gating.

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