Validation Flagging Correct Data

Your data appears correct, but Obvious is flagging it as an error, warning, or info issue. Here's how to diagnose and fix it.

The rule is checking the wrong field

What you see: A column you didn't expect is showing validation markers. The field name in the error message doesn't match what you intended.

What's happening: Validation rules use field keys, not display labels; if a rule targets a display label instead of the correct field key, Obvious will flag an unintended field.

How to fix it:

1. Identify the field key used by the rule and compare it to your sheet schema's actual column key.
2. Ask the agent to reapply the validation using the correct field key.

The custom check logic is inverted

What you see: Records with valid data are flagged, while records with bad data pass through clean.

What's happening: Custom validation rules use a validity predicate that should return true for correct data; if the logic is inverted, valid records are flagged and invalid ones pass.

How to fix it:

1. Review the custom rule's check expression; it should define correct data.
2. Flip the logic if it's inverted (e.g., value !== 'Inactive' to flag inactive records).

The severity level is misleading

What you see: Records show red error indicators, but the data is intentionally that way — like a phone number in a non-standard format your team uses internally.

What's happening: Validation severity defaults to "error," making correctly identified edge cases appear as critical issues when they are merely informational or warnings.

How to fix it:

1. Determine if the flag is a real problem or just informational.
2. Ask the agent to update the severity to "warning" or "info" as appropriate.

Auto-detected rules flagging valid data

What you see: You ran validation without specifying rules, and Obvious flagged records based on your sheet's field types or constraints — but the flags don't match your actual data standards.

What's happening: With auto-detect on, Obvious infers rules from your schema (e.g., email format for "email" fields); if your schema doesn't match actual data usage, auto-detected rules can be too strict.

How to fix it:

1. Update your sheet schema's field types or constraints to match your data standards.
2. Alternatively, rerun validation with auto-detect off and specify only needed rules.

Next steps

• Workbooks & Sheets Overview — how field types and schemas work.
• Formulas Returning Errors — fix formula issues that can feed bad data into validated fields.
• Import Errors & Data Mismatches — resolve data problems at the source.