What problem does it solve? Mutation testing produces noisy results: many survived mutants are harmless, while others reveal real test gaps. This Skill combines mutation testing, necessist test-statement removal, and Trailmark code graph analysis to classify findings into false positives, missing unit tests, and fuzzing targets. ## Core Features & Use Cases - Graph-informed triage: Maps each survived mutant to its containing function and uses caller counts, cyclomatic complexity, entrypoint reachability, and blast radius to classify it. - Multi-framework support: Covers mutmut, pytest-gremlins, Stryker, cargo-mutants, gremlins, PITest, Mull, slither-mutate, circomvent, cairo-mutants, and more, plus necessist for weak test detection. - Corroborated findings: When mutation testing and necessist flag the same production function, it is marked as the highest-confidence action item. - Use Case: After running cargo-mutants on a Rust parser and finding 30 survived mutants, use this Skill to identify which are dead code, which need boundary unit tests, and which entrypoint-reachable functions need fuzz harnesses. ## Quick Start Ask the agent to build a Trailmark graph of the target codebase, run the appropriate mutation testing framework and necessist, then triage all survived mutants into a GENOTOXIC_REPORT.md report.