Test-Selection Guard — Iron Law: No Test Chosen After Seeing the P-Value

Skill type: DISCIPLINE-ENFORCING. This is a thin discipline layer, not a stats engine. It does not run tests, fit models, or compute power — it forces the order of operations so the test is chosen by the data's shape, never by the result it produces. For the actual computation, hand off to the skills below.

REQUIRED BACKGROUND — this skill orchestrates, it does not reimplement:

• alterlab-statistical-analysis — runs the chosen test, the assumption checks (its assumption_checks.py: Shapiro-Wilk, Levene, Q-Q), power, and APA reporting.
• alterlab-statsmodels — fits the model (OLS/GLM/mixed/ARIMA) once the test is fixed.
• alterlab-scientific-thinking — judges design validity, biases, confounders upstream.
• alterlab-preregistration-discipline — the frozen analysis plan this gate presumes.

When the user needs execution, route there. This skill's whole job is what happens before the first scipy.stats call.