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Label Review Analytics — Duplicate Key Report + IQR Outlier Flags
x402
Label Review Analytics — Duplicate Key Report + IQR Outlier Flags 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 duplicate key report and IQR-based outlier detection on reviewed_records or changed_labels, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Duplicate key report + IQR outlier flags: Duplicate key report + IQR outlier flags 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 duplicate key report identifying rows with repeated row_id values, and (2) IQR outlier flags marking rows whose chosen numeric field (reviewed_records or changed_labels) falls outside the interquartile range bounds. Both reports are computed locally on the supplied data with no external lookups.
Example use cases
Annotation QA data quality audit
“I have 120 rows of label review logs with row IDs, dates, dataset groups, reviewed record counts, and changed label counts — can you check them for duplicate row keys and flag any IQR outliers in reviewed_records?”
Changed labels anomaly detection
“Here are my label review records for last month across three dataset groups. Can you run an IQR outlier check specifically on the changed_labels field and also tell me if there are any duplicate row IDs?”
Multi-group label review sanity check
“Before I submit this annotation batch, can you scan these 80 label review rows for any duplicate keys and identify statistically unusual values in reviewed_records using IQR outlier detection?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-065?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical data quality checks on label review records specifically — combining duplicate key detection and IQR-based outlier flagging in a single low-cost call. Ideal for annotation pipelines, ML data QA workflows, and pre-submission audits of up to 200 label review rows where no live prediction, external lookup, or professional assessment is required.
Side effects
- Exceeding 200 rows returns an error or truncates input
- Missing required fields (row_id, date, dataset_group, reviewed_records, changed_labels) causes validation failure
- Invalid date format (not YYYY-MM-DD) triggers schema validation error
- Numeric values outside the allowed range (-1T to +1T) are rejected
- Submitting fewer than 1 row causes a schema error
- All-null numeric columns may produce empty or degenerate IQR results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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