mutation-testing

Run mutation analysis to compute mutation score and detect surviving mutants.

Updated Jan 4, 2026
One-click install
npx skills add https://github.com/natea/ai-news-influencer --skill mutation-testing-natea
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mutation-testing
Source: https://github.com/natea/ai-news-influencer/tree/main/.claude/skills/mutation-testing
Command: npx skills add https://github.com/natea/ai-news-influencer --skill mutation-testing-natea

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Mutation testing validates the effectiveness of a test suite by introducing small code mutations and measuring how many are killed by tests. It helps identify weak tests and prove tests actually catch bugs.

Core Features & Use Cases

  • Automates generation of mutants and runs tests to compute mutation score.
  • Helps target critical code paths, improve assertions, and guide test improvements.
  • Use Case: Before critical releases, apply mutation testing to ensure high fault-detection capability.

Quick Start

Install the required mutation testing tools and run the mutation analysis to identify weaknesses and generate corrective tests.

Frequently Asked Questions about mutation-testing

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

FAQPage Schema
How does mutation testing measure test suite quality?

Mutation testing measures test suite quality by introducing small code mutations and calculating a mutation score based on how many mutants the tests kill. It detects surviving mutants to identify weak assertions and untested critical paths.

When should I run mutation analysis on my code?

You should run mutation analysis before critical releases to ensure high fault-detection capability. It validates that tests actually catch bugs by targeting critical code paths and verifying assertions across modules.

How do I track surviving mutants to improve test coverage?

You track surviving mutants by running mutation analysis against your code to identify where tests fail to catch introduced mutations. This guides automated test generation and helps prioritize corrective tests for weak areas.

Does mutation testing work with code coverage data?

Yes, mutation testing uses coverage data alongside mutation operators to validate test effectiveness. While code coverage shows executed lines, mutation analysis proves whether those executed tests actually assert correct behavior.

What's the best way to calculate mutation score for a software project?

The best way to calculate mutation score is to automate mutant generation and run tests against each mutation. The score reflects the percentage of mutants killed by tests, pinpointing exactly where assertions need improvement.