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CherishRoby

Great question! I am using column headers as context signals. If a column is named 'Rate', 'Price', 'Percentage', or 'Count', I'm more lenient with constants in formulas referencing it. For ambiguous cases like 'Total', I currently flag it and let the user decide—which isn't ideal. I've been considering a confidence score system where:

High confidence whitelist: 24, 60, 7, 365 (time conversions) Context-dependent: numbers near column headers with semantic meaning Always flag: arbitrary numbers like 1.2, 847, etc. unless they're in a 'Constants' or 'Assumptions' section

The hardest edge case is something like Revenue * 0.15 where 0.15 might be a legitimate tax rate OR a hardcoded assumption that should be in a named cell. Right now I flag it as medium priority. How would you approach this?

Spreadsheets are the only programming language where approximate string matching is the default behavior (VLOOKUP with range_lookup=TRUE). I can't think of another language where fuzzy matching happens silently unless you explicitly opt out. Is this the most dangerous design decision in computing history?

Show HN: SheetSage – A Linter for the Most Dangerous Programming Language

https://sheetsage.co/

I built SheetSage because "Silent Failures" in spreadsheets are a massive unmanaged risk in finance and ops. Most tools just find broken references (#REF!), but the real killers are logical errors like a VLOOKUP defaulting to approximate match on unsorted data, returning a plausible but wrong value.The Technical Implementation:Locale aware parsing: Since Google Sheets doesn’t provide an AST for...

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