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Label Review Analytics: Record Quality Audit + Exact Row Deduplication + Numeric Distribution
x402
Label Review Analytics: Record Quality Audit + Exact Row Deduplication + Numeric Distribution 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 bundled analytical reports on label review data: a record quality audit, exact row deduplication, and numeric distribution analysis for reviewed_records or changed_labels.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Record quality audit + Exact row deduplication + Numeric distribution: Record quality audit + Exact row deduplication + Numeric distribution 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
Returns three independent analytical reports: (1) a record quality audit flagging null, invalid, or malformed values; (2) an exact row deduplication report identifying fully identical rows; and (3) a numeric distribution summary (e.g. min, max, mean, percentiles, histogram) for either reviewed_records or changed_labels. All computed locally with no external lookups.
Example use cases
ML dataset label quality check
“I have up to 150 rows of label review records with columns row_id, dataset_group, date, reviewed_records, and changed_labels — can you audit their quality, find any exact duplicate rows, and show me the numeric distribution of the reviewed_records field all in one go?”
Deduplication before model retraining
“Before I retrain my model, I need to clean my label review batch — please run exact row deduplication plus a quality audit on these 80 records and also give me a distribution breakdown of changed_labels values.”
Cross-group label change analysis
“I've got label review data for two dataset groups over the past month, about 120 rows total. Can you check data quality, remove any duplicate rows, and show me how changed_labels values are distributed across the dataset?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-210?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three analytical operations on label review data in a single low-cost call ($0.01 USDC): a quality audit, exact deduplication, and numeric distribution. Ideal when your dataset is ≤200 rows, you have structured label review records with reviewed_records and changed_labels fields, and you want purely local computation with no external API calls or predictions. Prefer over separate single-report endpoints when you want all three insights bundled efficiently.
Side effects
- Exceeds 200-row limit — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, reviewed_records, or changed_labels) triggers validation error
- Null numeric values may reduce distribution report accuracy
- Invalid field enum value (not reviewed_records or changed_labels) causes error
- Empty rows array rejected by minItems:1 constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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