get_anomalies
Pre-computed, severity-ranked metric changes with a human-readable story attached to each one.
When to use it
The "what changed" question. Run it after a deploy, after a traffic shift, or as the first call of a weekly review.
Ask for it like this
You do not name the tool. These are questions that make an assistant reach for it:
What changed on my store in the last two weeks?
Did anything break after Tuesday's theme deploy?
How to read the result
- Each anomaly carries context about probable causes — nearby product changes, JS errors — so the story usually names the suspect.
- Sorted by severity. Read the criticals and ignore the tail unless one matches a hypothesis you already had.
Parameters
severity
Filter to low, medium, high or critical.
metricType
Filter to bounce_rate, conversion_rate, rage_click_rate, revenue or traffic.
entityType
Filter to page, funnel, product or store.
limit
Maximum anomalies to return.
Shared parameters it accepts
Documented in full on the tool reference index.
Date window — defaults to the last 30 days.
dateFrom
Start of the window, YYYY-MM-DD. Inclusive.
dateTo
End of the window, YYYY-MM-DD. Inclusive.
Every tool also accepts merchantId, which resolves from your connection. You never pass it.
What comes back
JSON. These are the top-level keys; date-scoped tools additionally carry a _meta block with the server date and the data coverage envelope.
anomalies
Severity-ranked changes, each with the metric, the entity, the magnitude and a narrative story.