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Label Review — String Normalisation + Base-100 Series
x402
Label Review — String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-03).
Runs two analytical reports on label review data: string normalisation of text fields and a base-100 indexed series for a chosen numeric measure, across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — String normalisation + Base-100 series: String normalisation + Base-100 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 analytical reports derived solely from the supplied data: (1) a string normalisation report cleaning and standardising text fields (dataset_group etc.), and (2) a base-100 indexed numeric series for the chosen field (reviewed_records or changed_labels), anchored to the specified base_index row. No external lookups or predictions are made.
Example use cases
Track label change rate trend
“I have a week of label review logs — 5 rows with dates, dataset groups, reviewed_records and changed_labels counts. Can you normalise the string fields and give me a base-100 series for changed_labels starting from the first row so I can see how the label change rate has evolved?”
Compare dataset group review volumes
“I've got label review records for two dataset groups over the past month — up to 50 rows with dates and reviewed_records counts. Run the string normalisation and base-100 index report using reviewed_records as the field, indexed from row 0, so I can compare group-a and group-b volume trends.”
QA check on annotation pipeline output
“Here are 30 rows from our annotation pipeline's label review export — each has a row_id, date, dataset_group, reviewed_records and changed_labels. Can you run both the string normalisation report and the base-100 series on reviewed_records starting at index 0, so I can QA the pipeline output?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-030?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review tabular data (up to 200 rows) and need two lightweight, offline analytical reports — string normalisation of categorical/text fields and a base-100 indexed numeric trend series — without needing live data lookups, ML predictions, or external integrations. It is cost-effective at $0.01 for both reports together and is ideal for QA pipelines, annotation monitoring dashboards, or exploratory analysis of label review exports.
Side effects
- Fewer than 1 or more than 200 rows submitted — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- base_index out of range (0–199) — error returned
- Numeric fields outside allowed range (±1 trillion) — validation failure
- Missing required fields (row_id, reviewed_records, changed_labels, date) — schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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