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Label Review Analytics — Grouped Numeric Summary & Daily Sum Series
x402
Label Review Analytics — Grouped Numeric Summary & Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Computes a grouped numeric summary and a daily sum time series for label review data (reviewed_records, changed_labels) supplied by the caller — up to 200 rows, two reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Grouped numeric summary + Daily sum series: Grouped numeric summary + Daily sum 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
Returns two independent analytical reports derived from the supplied label review rows: (1) a grouped numeric summary breaking down the chosen metric (reviewed_records or changed_labels) by dataset_group, and (2) a daily sum series aggregating that metric by date — all computed locally from user-supplied data with no external lookups.
Example use cases
Daily label change trend for ML team
“Here are our annotation logs for October — each row has a date, dataset group, reviewed_records, and changed_labels. Give me a daily sum series for changed_labels so I can see which days had the most label flips.”
Per-group review throughput breakdown
“I've got 120 rows of label review records across three dataset groups. Can you produce a grouped numeric summary on reviewed_records so I can compare throughput across groups?”
Combined audit report for annotation QA
“Run both a grouped numeric summary and a daily sum series on this label review dataset — field is changed_labels, up to 80 rows — I need both reports for our QA audit.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-089?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review or annotation audit data in row format and need both a group-level statistical summary and a date-level daily aggregation in a single low-cost call. It is ideal for ML ops teams tracking annotation throughput or label change rates across multiple dataset groups over time, without needing any external data enrichment or live lookups.
Side effects
- Exceeding 200 rows causes request rejection
- Missing required fields (row_id, date, dataset_group, reviewed_records, changed_labels) on any row causes validation error
- Invalid date format (not YYYY-MM-DD) triggers schema error
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array is not accepted (minItems: 1)
- Invalid field enum value (only 'reviewed_records' or 'changed_labels' accepted)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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