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Label Review Analytics: Grouped Numeric Summary + Trailing Mean Series
x402
Label Review Analytics: Grouped Numeric Summary + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Generates two offline analytical reports — a grouped numeric summary and a trailing mean series — for label review data containing reviewed_records and changed_labels fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Grouped numeric summary + Trailing mean series: Grouped numeric summary + Trailing mean series for supplied label review records (reviewed_records, changed_labels). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two analytical reports: (1) a grouped numeric summary aggregating reviewed_records and changed_labels statistics broken down by dataset_group, and (2) a trailing mean series computing rolling averages over the specified window for the chosen field — all computed locally from the supplied data with no external lookups.
Example use cases
Annotation team performance summary
“I have 150 rows of label review records from our annotation pipeline, each with a dataset group, date, and counts of reviewed_records and changed_labels. Can you give me a grouped numeric summary and a trailing mean series with window size 5 for reviewed_records so I can see how each team group is performing?”
Label quality drift detection
“We've been tracking changed_labels daily across two dataset groups over the last quarter. Can you compute the grouped numeric summary and a rolling mean with a window of 7 for changed_labels so I can spot if any group's label correction rate is drifting?”
Monthly review audit report
“I need two reports on our label review batch for October: a grouped breakdown of the numeric stats for reviewed_records by dataset_group, and a trailing mean series using a window of 4 — here are up to 200 rows with row_id, date, dataset_group, reviewed_records, and changed_labels.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-090?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review records with group identifiers and want both a grouped aggregate summary and a rolling mean trend report in a single paid call, without needing external data lookups, predictions, or professional assessments. It is ideal for ML annotation pipelines, data labeling QA workflows, and periodic review audits where up to 200 rows of local data need two complementary statistical views at minimal cost.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) on any row causes validation error
- Date field does not match YYYY-MM-DD pattern — rejected
- Window value outside [2, 200] range causes error
- Numeric fields outside [-1000000000000, 1000000000000] bounds are rejected
- Empty rows array rejected (minItems: 1)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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