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Label Review Analytics — Numeric Row Ordering & Keyed Dataset Comparison
x402
Label Review Analytics — Numeric Row Ordering & Keyed Dataset Comparison 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).
Analyzes label review records by sorting rows numerically and comparing two keyed datasets to surface differences in reviewed_records and changed_labels metrics.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Numeric row ordering + Keyed dataset comparison: Numeric row ordering + Keyed dataset comparison 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 numeric row ordering report that ranks the submitted rows by the selected field (reviewed_records or changed_labels), and (2) a keyed dataset comparison report that matches rows from the primary and secondary datasets by row_id and highlights value differences — all computed locally with no external lookups.
Example use cases
Auditing annotation session quality
“I ran two rounds of label review across groups A and B last week. Here are both datasets with row_id, date, dataset_group, reviewed_records, and changed_labels. Can you rank the rows by reviewed_records and compare the two rounds keyed by row_id to see which rows had different label change counts?”
Detecting label drift between annotation batches
“I have my original annotation batch and a re-reviewed batch, each about 80 rows with row IDs, dataset groups, dates, reviewed records, and changed labels. Please sort them numerically by changed_labels and do a keyed comparison to show me exactly which rows shifted between the two batches.”
Comparing dataset groups by review volume
“Here are two snapshots of our label review pipeline — one from last month and one from this month — both with row_id, dataset_group, date, reviewed_records, and changed_labels. Rank them by reviewed_records and compare them keyed by row_id so I can see which groups increased or decreased their review volume.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-123?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a ranked ordering of label review rows and a keyed side-by-side comparison of two label review datasets in a single API call. It is ideal for annotation quality audits, label drift detection between review rounds, and comparing dataset groups — all without any external data lookup or model inference. At $0.01 USDC for two reports covering up to 200 rows, it is cost-effective for batch label review analytics pipelines.
Side effects
- Missing required fields (row_id, dataset_group, date, reviewed_records, or changed_labels) causes validation error
- Exceeding 200 rows in either array returns a schema validation failure
- Invalid date format (not YYYY-MM-DD) triggers pattern mismatch error
- Numeric values outside allowed range (±1,000,000,000,000) are rejected
- Empty rows array (minItems: 1 not met) returns an error
- Invalid field enum value (anything other than reviewed_records or changed_labels) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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