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Label Review Analytics: Record Quality Audit + Exact Row Deduplication + Category Frequencies
x402
Label Review Analytics: Record Quality Audit + Exact Row Deduplication + Category Frequencies 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: record quality audit, exact row deduplication, and category frequency breakdown — all in one call for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Record quality audit + Exact row deduplication + Category frequencies: Record quality audit + Exact row deduplication + Category frequencies 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 identifying null values, out-of-range fields, and formatting issues; (2) exact row deduplication results flagging identical rows; and (3) category frequency counts showing how often each dataset_group appears and aggregate stats on reviewed_records and changed_labels.
Example use cases
ML annotation pipeline quality check
“I have label review logs from last week's annotation sprint — can you run a record quality audit, flag any exact duplicate rows, and show me how often each dataset group appears? Here's the data: row-1, 2026-10-01, group-a, 10 reviewed, 1 changed; row-2, 2026-10-02, group-b, 20 reviewed, 2 changed; row-3, 2026-10-01, group-a, 10 reviewed, 1 changed.”
Deduplication audit before model training
“Before I feed these label review records into training, can you check for exact duplicate rows and do a data quality audit on the set? I've got about 150 rows across group-alpha and group-beta with dates ranging from 2026-09-01 to 2026-09-30.”
Category frequency breakdown for team report
“Can you analyze my label review dataset and give me frequency counts by dataset_group so I know which groups have the most reviewed records? Also flag any quality issues. I have 80 rows spanning groups A, B, and C from October 2026.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-212?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three complementary data quality reports — quality audit, deduplication, and category frequencies — on label review data in a single low-cost call. It is ideal for ML teams managing annotation pipelines who want to validate and summarize tabular review logs without sending data to an external model or prediction service. Best for datasets up to 200 rows where all analysis is performed locally with no external lookups.
Side effects
- Input array exceeds 200 rows — request rejected with validation error
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause row-level validation failures
- Malformed date strings not matching YYYY-MM-DD pattern fail schema validation
- Empty rows array returns error; minimum 1 row required
- Null numeric values for reviewed_records or changed_labels may reduce audit coverage
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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