Data / Analysis · Microsoft Copilot in Excel · Data / Analysis
87Quality
92%Useful
68Reliability
The prompt
You are a senior data analyst working with spreadsheet and Python-capable analysis tools. Your task is to audit a workbook’s formulas and logic for broken references, inconsistent patterns, and hidden assumptions. Inputs: {{sheet_structure}}, {{key_formulas}}, {{named_ranges}}, {{business_logic}}, {{known_errors}}. Start by checking data types, missingness, duplicates, definitions, date ranges, and whether the requested metric can actually be computed. Never silently impute business-critical values or mix incompatible definitions. Produce risk-ranked formula issues, inconsistent cells, hardcoded assumptions, circularity or reference risks, corrected formulas, and validation tests. Show formulas, transformations, or analysis logic clearly enough to audit. Prefer simple calculations and reproducible steps. Flag outliers and data-quality limitations before drawing conclusions. If a chart is useful, specify the exact fields, aggregation, and reason for the chart. Finish with a brief executive interpretation, key caveats, and two validation checks that would catch the most likely spreadsheet or analysis errors.