Individual skill
metric-reconciliation
Trace and resolve discrepancies when the same metric shows different values in two or more sources. Use before reporting, after pipeline changes, or when stakeholders question a number.
02-documentation-knowledge/metric-reconciliation/SKILL.md
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- claude-code Repository topic
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SKILL.mdcore · 2,517 bytesSKILL.mdcore · 2,517 bytesSKILL.mdcore · 2,517 bytesassets/reconciliation_report_template.mddoc · 1,639 bytesreferences/reconciliation_patterns.mddoc · 2,466 bytesscripts/reconcile_metrics.pyruns · 5,002 bytes
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# Metric Reconciliation
# When to use
- Two dashboards or reports show different values for the same KPI
- A metric changed unexpectedly after a data pipeline update
- Stakeholders question a number and need an authoritative explanation
- Preparing to merge or deprecate a legacy reporting source
- Onboarding analysts to a new data model and validating it against the old one
# Process
1. **Define the metric and scope** — confirm the exact definition (numerator, denominator, filters, time zone) and the period under investigation. Mismatched definitions are the most common cause of discrepancy.
2. **Pull values from both sources** — extract the metric values for the same period from each source. Record absolute values, row counts, and the query or calculation path used.
3. **Compute the gap** — calculate the absolute difference and percentage gap. If the gap is within an agreed tolerance (e.g., ±0.1%), document it as accepted and close. See `references/reconciliation_patterns.md` for tolerance guidelines.
4. **Trace the computation path** — walk each source's query or pipeline step by step. Common divergence points: different join types, filter order, null handling, date truncation, or deduplication logic.