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Label Review — Record Quality Audit + Adjacent Row Changes
x402
Label Review — Record Quality Audit + Adjacent Row Changes 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 two analytical reports on label review data: a record quality audit and an adjacent-row change analysis, 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 + Adjacent row changes: Record quality audit + Adjacent row changes 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 record quality audit summarizing completeness, consistency, and anomalies in the supplied label review records, and (2) an adjacent row changes report showing how reviewed_records or changed_labels values shift between consecutive rows — all computed locally from the supplied data with no external lookups.
Example use cases
ML annotation quality audit
“I have 50 rows of label review logs from last month across three dataset groups, with reviewed_records and changed_labels counts per day. Can you run a record quality audit and show me the adjacent row changes so I can spot where labelers were inconsistent?”
Daily labeling pipeline QA check
“Run a quality audit and adjacent row change report on my labeling pipeline data for October — I've got 80 rows across group-a and group-b with daily reviewed_records and changed_labels values. Focus the analysis on changed_labels.”
Dataset group comparison for label drift
“I want to compare label drift between my two annotation dataset groups. Can you audit the record quality and show adjacent row changes for my 120 rows of review data, with dates from 2026-09-01 to 2026-10-31, analyzing the reviewed_records field?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-011?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need simultaneous record quality auditing AND adjacent row change detection on label review data (reviewed_records + changed_labels) for up to 200 rows in a single low-cost call. It is ideal for ML/annotation pipelines where you want to validate labeling consistency and detect row-to-row shifts without any external data lookups or live model predictions. Prefer it over general-purpose analytics tools when your data fits the label review schema and you want both reports in one operation for $0.01.
Side effects
- More than 200 rows submitted — request exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, reviewed_records, or changed_labels) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema rejection
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — validation error
- Empty rows array — minItems violation
- Invalid field selector (must be 'reviewed_records' or 'changed_labels') — enum validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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