Correlation vs Causation Validator

I observed {{metric_1}} and {{metric_2}} are {{correlation_strength}} correlated over {{time_window}}. Stakeholder claim: "{{stakeholder_claim}}"

Assess causal validity:
1. Temporal ordering — does {{metric_1}} lead {{metric_2}}?
2. Confounders — what variables could explain both (seasonality, user cohort, external event)?
3. Reverse causality — could {{metric_2}} cause {{metric_1}}?
4. Correlation strength — how sensitive is the relationship to time lag or aggregation level?
5. Plausible mechanism — is there a business reason for causality?

Recommend: accept claim / reject / test with A/B experiment. Propose experiment design if needed.