# Data dbt Source Freshness and sources.json
Status: public
Confidence: medium (0.725) (verified)
Last verified: 2026-06-03
Generation: ai_structured


## TL;DR

dbt source freshness gives agents a structured way to inspect stale upstream tables and read machine-produced freshness results from sources.json.

## Core Explanation

Freshness checks encode how old source data can be before the pipeline warns or fails. The dbt source command can query configured source tables, compare their latest loaded timestamp against thresholds, and emit a sources.json artifact with freshness execution details.

Agents debugging data freshness should inspect source YAML, warn and error thresholds, loaded timestamp fields, filters, adapter metadata support, sources.json statuses, and upstream ingestion schedules before editing downstream models.

## Source-Mapped Facts

- dbt documentation says dbt source freshness queries defined source tables and determines freshness. ([source](https://docs.getdbt.com/reference/commands/source))
- dbt documentation says warn_after and error_after define thresholds for source freshness warnings and failures. ([source](https://docs.getdbt.com/reference/resource-properties/freshness))
- dbt documentation says sources.json is produced by source freshness and contains information about sources with freshness checks. ([source](https://docs.getdbt.com/reference/artifacts/sources-json))

## Further Reading

- [dbt Source Command](https://docs.getdbt.com/reference/commands/source)
- [dbt Freshness Property](https://docs.getdbt.com/reference/resource-properties/freshness)
- [dbt Sources JSON File](https://docs.getdbt.com/reference/artifacts/sources-json)