What problem does it solve? Test suites often look healthy while hiding weak assertions, tautological tests, flaky behavior, and untested error paths. This Skill audits a suite on three separate axes — design quality, completeness, and efficacy — so you can see whether your tests would actually catch bugs. ## Core Features & Use Cases - Farley Index scoring: Rates eight test properties (Understandable, Maintainable, Repeatable, Atomic, Necessary, Granular, Fast, First) on a weighted 0-10 scale with file:line evidence for every score. - Tautology theatre detection: Finds mock tautologies, trivial asserts, framework tests, and source-text guards that pass regardless of production code. - Coverage and efficacy reviews: Hunts behavior gaps manually, runs coverage tools (cargo llvm-cov, pytest --cov, vitest, JaCoCo) when available, and triages mutation-testing survivors into real gaps versus equivalent mutants. - Use Case: Ask for a review of your Rust or Python test suite and receive a structured report with the Farley Index, worst offenders, ranked recommendations, uncovered behavior spans, and weak assertions that mutation testing would expose. ## Quick Start Review the test suite in this repository and produce a Farley Index report with coverage and efficacy findings.
