Introduction to the Positive Check
The Positive check asserts that every value in a numeric field is strictly greater than zero. Zero itself is rejected. Use it on quantities, amounts, and measures that have no meaning at or below zero.
This section is the complete guide to the check. The Deep Dive covers the definition, properties, and full evaluation semantics, explains how anomalies are reported, walks through production examples, and collects best practices; the How-tos are step-by-step tutorials for creating, editing, and deleting a check; the API page documents the payload for programmatic use; and the FAQ answers the most frequent questions.
Next Steps
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How It Works
The complete reference: definition, field scope, the comparison, NULL handling, arrays, filter behavior, and coverage.
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Anomaly Reporting
The anomaly messages the check produces, what the numbers mean, Source Records highlighting, and Custom Anomaly Description.
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Examples
Three production scenarios with sample data, anomaly messages, and the SQL equivalent of what the check evaluates.
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Best Practices
Guidelines for choosing between the sign rules, pairing them, and keeping the signal clean.
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Permissions
The team permission each action needs: view, create, edit, archive, restore, and delete.
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Create a Check
Step-by-step tutorial for creating Positive check on a numeric field.
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Edit a Check
Step-by-step tutorial for changing the target field, filter, coverage, or organizational properties.
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Delete a Check
Step-by-step tutorial for archiving a check and deleting it permanently.
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Troubleshooting
Common problems with zero, NULLs, arrays, and anomaly reporting, and how to resolve them.
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API
Payload shape and field notes for creating Positive check programmatically.
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FAQ
Short answers to questions about zero, NULLs, arrays, and anomaly reporting.