# Missing vs zero vs stale

Prompt · Data integrity and analytics · D01

Finds where 'we don't know' turns into 0 and then into a wrong total.

## Prompt

```text
Identify where the application confuses missing, zero, unavailable, estimated, stale, and not applicable. Trace the consequences through storage, calculations, and presentation.
```

**What it returns:** Each field with how each absence state is stored, how calculations treat it, and how it displays.

**Skip it when:** Data with no optional values.

**Tools:** Repository and read-only database access.

**Changes:** Changes nothing

**Sessions:** Look first, then fix in a new session

## Related

- [Fallbacks that look like real data](https://atlasscope.dev/prompts/fallbacks-that-look-like-real-data): Finds screens that show a confident zero or an empty list when the real answer is 'we could not load this'.
- [Where did this number come from?](https://atlasscope.dev/prompts/where-did-this-number-come-from): Checks that every number on screen can be traced back to a source document.
- [Rounding and unit mix-ups](https://atlasscope.dev/prompts/rounding-and-unit-mix-ups): Finds money and percentage values that change scale or lose precision along the way.

Source: https://atlasscope.dev/prompts/missing-vs-zero-vs-stale