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Label Review — Daily Sum Series + Adjacent Row Changes
x402
Label Review — Daily Sum Series + Adjacent Row Changes 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 daily sum time series and adjacent row change analysis for label review data (reviewed_records and changed_labels) over up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Daily sum series + Adjacent row changes: Daily sum series + Adjacent row changes 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 analytical reports: (1) a daily sum series aggregating the selected field (reviewed_records or changed_labels) by date, and (2) an adjacent row change analysis showing the difference between consecutive rows — both computed locally from the supplied data with no external lookups.
Example use cases
Daily annotation activity trend report
“I have 150 rows of label review data with dates, dataset groups, reviewed_records, and changed_labels — can you give me a daily sum series and row-over-row change breakdown for reviewed_records so I can see how annotation volume trended this month?”
Spotting label correction spikes
“I want to audit our changed_labels field across these label review records — can you run a daily sum series and adjacent row change report on changed_labels to help me spot days where corrections spiked?”
Comparing two dataset groups over time
“Here are my label review rows split across group-a and group-b with dates and reviewed_records counts — run the daily sum series and adjacent row changes report on reviewed_records so I can compare how each group tracked day by day.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-137?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular label review data with dates and want both a daily aggregation trend and a row-level sequential diff in a single low-cost call. It is ideal for ML annotation QA pipelines, labeling audit workflows, or any scenario where you need to monitor daily reviewed_records or changed_labels patterns without any external data lookup or prediction.
Side effects
- Input exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes parsing failures
- Null values in the selected numeric field may produce incomplete aggregations
- Unsupported field enum value causes schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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