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Label Review Analytics: Record Quality Audit + Exact Row Deduplication + Duplicate Key Report
x402
Label Review Analytics: Record Quality Audit + Exact Row Deduplication + Duplicate Key Report 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).
Runs three local analytical reports on label review data: a record quality audit, exact row deduplication, and a duplicate key report — all from supplied data, no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Record quality audit + Exact row deduplication + Duplicate key report: Record quality audit + Exact row deduplication + Duplicate key report for supplied label review records (reviewed_records, changed_labels). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Three independent reports: (1) a record quality audit highlighting data issues in the supplied rows, (2) exact row deduplication results identifying and removing fully duplicate rows, and (3) a duplicate key report listing row_ids or key combinations that appear more than once — all computed locally from the submitted data with no external lookups.
Example use cases
ML annotation pipeline quality gate
“I've got a batch of up to 150 label review records from our annotation pipeline — each row has a row_id, dataset_group, date, reviewed_records count, and changed_labels count. Can you audit them for record quality issues, find any exact duplicate rows, and flag any duplicate keys so I can clean the dataset before training?”
Label review dataset deduplication before export
“Before I export this week's label review data to our data warehouse, can you run exact row deduplication and a duplicate key report on my 80 rows? Each row has a row_id, dataset_group, date, reviewed_records, and changed_labels. I want to make sure there's no junk going in.”
Spot-check changed_labels data integrity
“We had a data ingestion glitch and I suspect some label review records got duplicated. Can you do a record quality audit and duplicate key report on these 60 rows — row_id, dataset_group, date, reviewed_records, changed_labels — to confirm whether we have bad data?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-209?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three data quality operations — record quality audit, exact deduplication, and duplicate key detection — on a single label review dataset in one low-cost call. It is ideal for ML/annotation teams validating label review batches before downstream use. Prefer it over separate single-report endpoints when all three checks are needed together for cost and simplicity. Not suitable when you need live lookups, predictions, or analysis of datasets larger than 200 rows.
Side effects
- Submitting more than 200 rows will exceed the row limit and may result in an error or truncation
- Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) will cause validation failure
- Date values not matching YYYY-MM-DD pattern will be rejected
- Non-numeric values for reviewed_records or changed_labels will fail schema validation
- Empty array submission (minItems: 1 not met) will return an error
- Payment failure or insufficient USDC balance will block the call
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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