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Label Review — Record Quality Audit + Exact Row Deduplication
x402
Label Review — Record Quality Audit + Exact Row Deduplication 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 analytical reports on label review data: a record quality audit and exact row deduplication, for up to 200 rows of reviewed_records and changed_labels data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Record quality audit + Exact row deduplication: Record quality audit + Exact row deduplication 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 record quality audit highlighting data issues such as nulls, out-of-range values, or malformed fields in the reviewed_records and changed_labels columns; and (2) an exact row deduplication report identifying rows that are identical across all fields. No external lookups or predictions are made — all analysis is performed locally on the supplied data.
Example use cases
ML annotation data quality check
“I have a batch of label review records from our annotation team — each row has a date, dataset group, number of reviewed records, and changed labels. Can you audit them for quality issues and flag any exact duplicate rows? I'll send you up to 150 rows.”
Deduplication before label aggregation
“Before I aggregate our label review stats by dataset group, I want to make sure there are no duplicate rows in the export. Can you run an exact row deduplication report on these records — they have row IDs, dates, group names, reviewed_records, and changed_labels columns?”
Validating label review pipeline output
“Our labeling pipeline spit out a CSV of reviewed records with changed_labels counts per day and group. Can you do a record quality audit on it and also check if any rows are exact duplicates? There are about 80 rows across group-a and group-b.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-002?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap ($0.01 USDC), offline-only dual-report check on label review tabular data — specifically combining a record quality audit with exact row deduplication in a single call. Ideal for ML/annotation pipelines where you want to validate reviewed_records and changed_labels fields before aggregation or downstream processing. Not suitable if you need fuzzy deduplication, predictive analytics, external data enrichment, or processing more than 200 rows.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, reviewed_records, changed_labels) — validation error
- Malformed date format (not YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (-1T to 1T) — rejected
- Empty input array — rejected with minItems violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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