What problem does it solve? AI-generated and hand-written tests often look complete but are fake: they mock the systems they claim to test end-to-end, silently pass when features are broken, or assert values the test itself injected. This Skill enforces specification-driven test quality so that a passing suite actually proves the software works. ## Core Features & Use Cases - Seven quality gates: Gherkin scenario coverage, no internal mocks in live categories, no silent-pass patterns, real behavior assertions, Test Plan ↔ DoD parity, adversarial regression cases for bug fixes, and no self-validating test setups. - Per-category test taxonomy: Defines what "real" means for unit, functional, integration, ui-unit, e2e-api, e2e-ui, stress, and load tests, including grep-based scans for interception patterns like page.route, cy.intercept, msw, and nock. - Structured verification workflow: An eight-step audit sequence plus a decision tree that classifies any test as REAL, FAKE, SELF-VALIDATING, PROXY, MOCKED, SILENT-PASS, or TAUTOLOGICAL. - Use Case: Before marking a bug fix done, run the Skill's checks to confirm at least one regression test uses adversarial input that would fail if the bug returned, and that no early-return bailout hides a redirect to the login page. ## Quick Start Review the tests in this scope against the Gherkin scenarios and flag any that are mocked, silent-passing, or self-validating.