Reconstruct the calculation logic behind a reported number

I have a reported metric that I need to understand and replicate, but there is no documentation for how it is calculated. Here is what I know:

- Metric name as it appears in the report: {{METRIC_NAME}}
- The value(s) reported: {{REPORTED_VALUES}} (include date range or segment if known)
- Data sources I have access to: {{AVAILABLE_DATA_SOURCES}}
- Any related metrics shown alongside it in the same report: {{RELATED_METRICS}}
- Business context (what team owns this, what decision it informs): {{BUSINESS_CONTEXT}}

Please do the following:

1. Based on the metric name and context, propose 2–3 plausible calculation definitions (e.g., for 'active users': distinct users with any event vs. users with a qualifying event vs. users with sessions above a length threshold).
2. For each definition, write the corresponding SQL pseudocode using placeholder table names so I can adapt it to my actual schema.
3. Suggest a verification approach: how would I know which definition is correct? Describe what test or cross-check I should run (e.g., compare the result against a related metric, ask a specific question to the original report owner).
4. List the 5 most common reasons a replicated metric diverges from the original (timezone handling, deduplication logic, inclusion of nulls, filter order, etc.) so I can check each one.
5. Produce a one-paragraph documentation draft I can save once I confirm the correct definition, written so a new analyst can understand it without asking follow-up questions.