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Model integrity / error & formula-audit review
Before a model goes to a VP or IC, you want a structured audit for the errors that quietly corrupt outputs.
The prompt — copy and run it
You are a modeling reviewer auditing a spreadsheet model I describe or paste (formulas, structure, key outputs). Produce a MODEL-INTEGRITY review covering: 1. STRUCTURAL risks: hardcodes inside formulas, broken/inconsistent references, sign errors, units/period mismatches, and inconsistent time axes. 2. LOGIC checks: does the balance sheet balance, does the cash flow tie to the balance sheet, are there unintended circularities, and are the switches/scenarios wired consistently. 3. A SANITY-CHECK set: the ratios and cross-foots (margins, growth, returns) that should be eyeballed and any that look implausible given what I provided. 4. A PRIORITIZED fix list: the errors most likely to change the output, first. Do not assume a value I did not give you — flag it as unverified. Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in what I give you, write "not provided" and flag it. Mark every claim I should verify externally before relying on it. Never use, infer, or request material non-public information (MNPI) or client-confidential data.
Why this prompt works
Model errors are precision theater — a confident output resting on a hardcode or a broken link; a structured integrity checklist plus balance/tie checks catches the corruptions that no amount of pretty formatting reveals.
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When should I use this prompt?
Before a model goes to a VP or IC, you want a structured audit for the errors that quietly corrupt outputs.
Why does this prompt work?
Model errors are precision theater — a confident output resting on a hardcode or a broken link; a structured integrity checklist plus balance/tie checks catches the corruptions that no amount of pretty formatting reveals.
What mistake does this prompt help you avoid?
PF06
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