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Label Review Analytics — String Normalisation + Daily Sum Series
x402
Label Review Analytics — String Normalisation + 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).
Runs two local analytical reports (string normalisation and daily sum series) on label review data containing reviewed_records and changed_labels fields, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — String normalisation + Daily sum series: String normalisation + 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
Two analytical reports generated locally without any external lookups: (1) a string normalisation report standardising string fields across the supplied label review rows, and (2) a daily sum series aggregating the selected numeric field (reviewed_records or changed_labels) by date — covering up to 200 input rows.
Example use cases
Daily trend in annotation corrections
“I've got 50 rows of label review records from my ML annotation team, each with a date, dataset group, and counts of reviewed records and changed labels — can you produce the daily sum series for changed_labels so I can see which days had the most corrections?”
String normalisation across dataset groups
“My label review export has inconsistent string formatting in the dataset_group field across about 80 rows dated through October 2026 — can you run the string normalisation report on the reviewed_records field to clean those up?”
Dual-report label audit for QA pipeline
“We just finished a labeling sprint and I have 120 rows of audit data with date, group, reviewed_records, and changed_labels — run both the string normalisation and daily sum reports on changed_labels so we can share the summary with the QA team.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-027?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and a daily sum time series computed together on label review or annotation audit data in a single low-cost call, without requiring any external data enrichment, prediction, or live lookups. It is ideal for offline or batch post-processing of annotation pipeline exports up to 200 rows where the two bundled reports (normalisation + daily aggregation) match your analytical need.
Side effects
- Input exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside [-1,000,000,000,000, 1,000,000,000,000] are rejected
- Invalid field selector (not 'reviewed_records' or 'changed_labels') causes error
- Empty rows array is rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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