Query Analytics
query_analyticsRead-onlyIdempotent
Aggregate evaluation metrics across time and dimensions to uncover quality trends and identify issues, helping refine evaluation strategies.
Instructions
Query Okareo's product analytics to understand evaluation trends.
Answers questions like "how is my evaluation quality trending" by
aggregating measures across dimensions over a time window.
Args:
measures: Metrics to aggregate. Required. For the ``check_trend``
cube: avg_check_value, issue_rate, error_rate, datapoint_count,
issue_count, error_count, test_run_count, avg_latency, sum_cost,
input_token_count, output_token_count.
dimensions: Optional group-by fields (e.g. ["check.name"],
["target.name"], ["provider"]).
cube: Optional analytics cube name (defaults to ``check_trend``,
currently the only cube).
filters: Optional list of filter objects
``{"member": ..., "operator": ..., "values": [...]}``.
time_range: Optional look-back window — one of LAST_HOUR,
LAST_24_HOURS, LAST_7_DAYS, LAST_14_DAYS, LAST_30_DAYS,
LAST_90_DAYS. If neither time_range nor time_dimensions is
given, defaults to LAST_30_DAYS (the analytics API requires a
time window).
time_dimensions: Optional time bucketing — a list with at most one
entry, e.g. [{"dimension": "test_run.start_time",
"granularity": "day"}] (granularity: hour, day, or week).
include_metadata: When true, also return the available cubes,
dimensions, and measures so the query can be refined.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| cube | No | ||
| filters | No | ||
| measures | Yes | ||
| dimensions | No | ||
| time_range | No | ||
| time_dimensions | No | ||
| include_metadata | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |