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Label Review Analytics — Duplicate Key Report + Date by Category Pivot
x402
Label Review Analytics — Duplicate Key Report + Date by Category Pivot 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).
Analyzes label review records to produce two reports: a duplicate key detection report and a date-by-category pivot table, for up to 200 rows of supplied data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Duplicate key report + Date by category pivot: Duplicate key report + Date by category pivot 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 independent analytical reports: (1) a duplicate key report identifying any repeated row_id values in the supplied label review records, and (2) a date-by-category pivot table aggregating the selected field (reviewed_records or changed_labels) across dates and dataset_group categories — all computed locally from supplied data with no external lookups.
Example use cases
Annotation QA duplicate key audit
“I've got a batch of label review records and I need to know if any row IDs are duplicated before I merge them into production — can you run a duplicate key report on my reviewed_records data? It has fields: row_id, dataset_group, date, reviewed_records, and changed_labels.”
Date-category pivot for label change tracking
“Can you pivot my label review dataset by date and dataset_group so I can see how changed_labels breaks down across categories over time? I'll supply the rows with row_id, dataset_group, date, reviewed_records, and changed_labels — up to 200 rows.”
Dual-report QA for ML annotation sprint
“We just finished an annotation sprint and I need two quick reports on our label review output: first, flag any duplicate row IDs, and second, show me a date-by-category pivot of reviewed_records. Can you run both on the same dataset of up to 200 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-068?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review or annotation data (up to 200 rows) and need both a duplicate key audit and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal for ML data pipeline QA workflows where you want to validate row uniqueness and summarize metrics by date and group simultaneously, without needing any live data lookups or external enrichment.
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) cause row-level validation errors
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- Numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array fails minItems:1 constraint
- Invalid field enum value (not 'reviewed_records' or 'changed_labels') causes parameter rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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