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Label Review Analytics — Duplicate Key Report + Grouped Numeric Summary
x402
Label Review Analytics — Duplicate Key Report + Grouped Numeric Summary 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 a duplicate key report and a grouped numeric summary for reviewed_records or changed_labels fields, covering up to 200 rows in one call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Duplicate key report + Grouped numeric summary: Duplicate key report + Grouped numeric summary 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: (1) a duplicate key report identifying any row_ids that appear more than once in the submitted data, and (2) a grouped numeric summary of the selected field (reviewed_records or changed_labels) aggregated by dataset_group — covering up to 200 input rows.
Example use cases
Auditing annotation batch for duplicates
“I exported a batch of label review records from our annotation pipeline — can you check for any duplicate row IDs and give me a grouped summary of reviewed_records broken down by dataset_group?”
Tracking changed labels across dataset groups
“Here's a CSV worth of label review data with up to 150 rows. I want to see if there are any duplicate keys and get a grouped numeric summary of the changed_labels field by group.”
Data quality check before model training
“Before we feed this label review batch into training, can you run a duplicate key report and a grouped summary on the reviewed_records values, grouped by dataset_group, for these 80 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-056?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously audit label review data for duplicate row keys AND get a grouped numeric breakdown of a chosen metric (reviewed_records or changed_labels) by dataset_group — all in a single low-cost call against your own supplied data, with no external lookups or predictions involved. It is ideal for ML data ops teams validating annotation batches before training runs.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) cause row-level errors
- Invalid date format (non-YYYY-MM-DD) causes validation failure
- Numeric values outside the allowed range cause schema rejection
- Empty rows array returns an error
- Invalid field selector (not 'reviewed_records' or 'changed_labels') causes failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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