What problem does it solve? Passing tests do not prove a test suite actually catches bugs. This Skill reveals hidden gaps in test coverage by introducing small deliberate bugs (mutations) into Python source code and checking whether any test fails, exposing weak spots that line coverage metrics miss. ## Core Features & Use Cases - Systematic Mutation Catalogue: Applies 8 proven mutation types including negated conditions, changed boundaries, swapped return values, and deleted side effects. - Mutation Score Reporting: Produces a summary table with killed/survived results, a mutation score percentage, and diagnostic quality ratings for each failure. - Test Recommendations: For every survived mutation, describes a concrete test that would catch it, and can optionally implement the missing tests. - Use Case: Before shipping a critical payment module, run mutation testing on it to discover that your tests never verify the boundary condition on the discount calculation, then add the recommended test. ## Quick Start Ask the AI to run mutation testing on a specific Python file or directory to assess how strong its test suite really is.