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Build a Pre-Launch PMF Threshold Register

The founder gets a structured PMF threshold register that fixes the metrics, their pass thresholds, and the false-positive traps in advance, so the later PMF call is measured against pre-committed bars instead of post-hoc rationalization.

You receive: A JSON object: { metrics: [{ metricId, name, metricType: enum(survey|retention|activation|revenue|referral), threshold: number, unit: enum(percent|count|days|ratio), measurementWindow }], falsePositives: [{ pattern, whyItMisleads }], sets BeforeLaunch: bool, seanEllisIncluded: bool }

Part of Choose Business Model

What's verified: STUD verifies the register is structurally complete and that the named guardrails exist: minimum metric count, a Sean-Ellis-style survey threshold at >=40%, Day-7/Day-30 retention metrics, and defined false-positive patterns. STUD does NOT measure the product's actual retention or run the survey; it does NOT decide whether the chosen thresholds are the correct PMF bar. It checks that pre-committed, structurally valid thresholds were authored, not that PMF was achieved.