genotoxic

Name: genotoxic
Availability: InStock
Author: rohanbhatia27

Analyze mutation testing results to classify survived mutants into actionable categories.

1|Updated Apr 7, 2026

Search Tags:#code analysis #mutation testing #triage #graph analysis #fuzzing

Ready to run

npx skills add https://github.com/rohanbhatia27/rohanstutoring-redesign --skill genotoxic-rohanbhatia27

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: genotoxic
Source: https://github.com/rohanbhatia27/rohanstutoring-redesign/tree/main/.agents/skills/genotoxic
Command: npx skills add https://github.com/rohanbhatia27/rohanstutoring-redesign --skill genotoxic-rohanbhatia27

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires trailmark, mutation testing framework, necessist, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill simplifies the process of analyzing code mutation testing results, enabling developers to quickly identify and address false positives, missing test coverage, and potential fuzzing targets.

Core Features & Use Cases

Survived Mutant Triage: Classify survived mutants into actionable categories: false positives, missing unit tests, and fuzzing targets.
Mutation Testing Integration: Integrate with various mutation testing frameworks and necessist for comprehensive analysis.
Graph Analysis: Utilize code graph data to inform triage decisions, enhancing the accuracy of the analysis.
Use Case: After running mutation testing, use this Skill to prioritize and focus on the most critical issues in your codebase.

Quick Start

Analyze the mutation testing results of your project using the 'genotoxic' skill.

Frequently Asked Questions about genotoxic

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

FAQPage Schema

How do I triage survived mutants from code mutation testing?▼

To triage survived mutants from code mutation testing, you classify them into actionable categories like false positives, missing unit tests, and fuzzing targets. This Skill uses code graph data to inform these triage decisions and prioritize critical issues.

What is the best way to identify false positives in mutation testing results?▼

Identifying false positives in mutation testing results is handled by analyzing code graph data alongside your mutation testing framework outputs. This approach classifies survived mutants to separate false positives from genuine missing test coverage.

Does mutation testing triage work with necessist?▼

Yes, mutation testing triage works with necessist. The analysis integrates with necessist and various mutation testing frameworks to provide comprehensive language-specific analysis of your codebase results.

Do I need Trailmark to analyze mutation testing results?▼

Yes, you need Trailmark to analyze mutation testing results with this approach. Trailmark is a required dependency for utilizing code graph data to inform triage decisions and identify potential fuzzing targets.

Can I identify fuzzing targets from survived mutants?▼

Yes, you can identify fuzzing targets from survived mutants. By classifying survived mutants into actionable categories, the analysis highlights areas in the codebase that are potential candidates for targeted fuzzing.