What problem does it solve?
This Skill helps you design, review, and repair tests that actually protect behavior instead of merely boosting coverage or mirroring implementation details. It gives you a clear doctrine for choosing the right test layer, avoiding brittle selectors, reducing flakiness, and preventing mock-driven confidence in both human-written and AI-generated tests.
Core Features & Use Cases
- Test placement and boundary decisions: Decide whether a case belongs in unit, integration, route, or end-to-end testing based on the invariant being protected.
- Test quality review: Identify brittle selectors, hidden shared state, static sleeps, weak assertions, over-mocking, and other failure modes.
- AI test generation guardrails: Apply mandatory gates for agent-written tests, including invariant-first setup, real execution, and negative companions.
- CI and flakiness discipline: Handle flaky tests with quarantine, ownership, deterministic design, and quality probes like mutation testing.
- LLM and agent evaluation: Build stronger evals for RAG, tool use, and agent workflows using oracle ladders and outcome-based scoring.
- Use case: When a new feature, failing test, or flaky suite needs diagnosis, this Skill helps you choose the right fix and the right test shape before touching code.
Quick Start
Ask for a test review or new test plan by naming the invariant, the owning layer, and the canonical suite, then let the Skill guide the rest.