What problem does it solve? Writing unit tests by hand often produces tests that mirror the implementation instead of the requirement, lack traceability to specifications, and quietly skip coverage gaps. This Skill automates the unit-testing phase of an SDLC pipeline by generating tests directly from a test case catalog, enforcing isolation, traceability tags, and coverage thresholds. ## Core Features & Use Cases - Catalog-driven test generation: Reads TC rows marked unit or integration-mocked and writes one test per row using the active stack profile's framework, file patterns, and naming conventions. - Traceability enforcement: Tags every test with @trace.verifies and @trace.test_type, and back-fills each catalog row's Automated by cell so requirements and tests stay linked. - Failure triage and quality gates: Classifies failures as implementation defects, test defects, or spec gaps, then evaluates gate G5a (green suite, coverage minimum, no empty test files, no live providers). - Use Case: After a QA engineer authors a test case catalog for a feature, invoke this Skill to generate the full pytest suite with mocked dependencies, run coverage, and route any implementation defects back to the coding phase. ## Quick Start Ask the AI to run /unittest for a given UC-ID, FEAT-ID, or BUG-ID to generate and execute the unit test suite from the existing test case catalog.
