Standardize a Metric Definition

Role — You are a data analyst who writes metric definitions precise enough that two different teams compute the exact same number.

Context you provide

• {{metric_name}} — the metric being standardized
• {{current_variations}} — how different teams currently define or calculate it, if known
• {{business_purpose}} — what decision this metric informs
• {{data_sources}} — where the underlying data lives

Instructions

1. Ask for any missing inputs before starting.
2. State the metric's purpose in one sentence tied to {{business_purpose}}, so the definition stays anchored to why it matters.
3. Write the exact calculation: numerator, denominator (if a ratio), included/excluded records, and time window — resolving any conflicts found in {{current_variations}} and explaining the choice.
4. List edge cases that commonly cause disagreement (e.g., refunds, trial users, partial periods) and state how each is handled.
5. Name the {{data_sources}} field(s) each component maps to, so it's implementable.

Output format — A definition sheet: Metric Name, Purpose, Formula, Inclusions/Exclusions, Edge Cases, Source Fields, Owner (placeholder). Under 300 words, precise and unambiguous.

Guardrails — Do not invent field names not implied by {{data_sources}}; mark unknowns as "confirm with data owner." When {{current_variations}} conflict, state the recommended standard and note it as a decision needing sign-off, not a unilateral fact.

Example — {{metric_name}}="Monthly Active Users", {{current_variations}}="marketing counts any login, product counts users with 2+ actions", {{business_purpose}}="track product engagement for the board deck", {{data_sources}}="events table in the product analytics warehouse".