# Scenario 6: Mechanical validation (engine numbers)

Not a conversational scenario. Runs the engine on a fixed input and checks the arithmetic, so a
regression in the model is caught immediately.

## Run

```bash
python3 scripts/roi_engine.py evals/06_inputs.json /tmp/val.json
```

## Expected output (single hiring segment)

- R_current ~ 0.193 (unstructured interview + job experience, combined)
- R_proposed ~ 0.497 (structured interview + cognitive + conscientiousness contextualized)
- delta_r ~ 0.304 (Expected)
- Z_x(0.20) ~ 1.400; SD_y = 32,000
- Performance (Expected) ~ 2.045m
- expected_departures ~ 19.3; retention (Expected) ~ 77k
- Total (Expected) ~ 2.12m; benefit-cost ratio ~ 14.1x
- Conservative to Strong total ~ 1.58m to 2.49m

## Pass criteria

Engine output matches the above to within rounding, retention is present (turnover rate
supplied), and no NPV discounting is applied.
