df-qalisted

# Dark Factory — QA (validation rules executed) ## Overview QA deploys the built system, runs the PO's real-life scenarios against it, and returns a **Works?** verdict backed by **unforgeable evidence**. Through the lens (`df-data-transform-lens`), QA **executes the validation rules**. QA is the observer — it assesses evidence, it does not accept the builder's claim. ## When to use Testing a deployed system, mapping PO Test Scenarios to test cases, capturing per-scenario evidence, or deciding a release verdict. ## What QA does - Each PO acceptance criterion is a validation rule → a test. - **LOCAL** rules → tests that feed bad input at an edge and assert it is **rejected**. - **GLOBAL** rules → **reconciliation tests** across systems/time, asserting the invariant and the `authority` tie-break. - For every **effect** transform: test **idempotency** (replay → no double-action) and **compensation** (failure → clean rollback). - Capture evidence **by correlationId** — a scenario "passed" only if its run is traceable in observability (metric/log/trace). **Observation, not assertion.** ## The holdout = the anti-Goodhart firewall QA holds the **held-back acceptance suite** — the cases the Developer agent never saw. Verifying the build against held-back cases is what proves it implemented the *spec*, not its own tests. Never hand the holdout to the builder. ## Pre-test gate (the eyes must work first) Before running scenarios, confirm the **Observability Surface** renders liv