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Label Review — Equal-Width Histogram + IQR Outlier Flags
x402
Label Review — Equal-Width Histogram + 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 2026-10-24).
Generates an equal-width histogram and IQR-based outlier flags for label review records (reviewed_records and changed_labels fields), producing 2 independent analytical reports from supplied data up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Equal-width histogram + IQR outlier flags: Equal-width histogram + 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
Two independent analytical reports: (1) an equal-width histogram showing bin ranges and counts for the selected field (reviewed_records or changed_labels), and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range bounds — all computed locally from the supplied data with no external lookups.
Example use cases
Annotation pipeline quality audit
“I have 120 rows of daily label review logs with reviewed_records and changed_labels columns — can you bin the reviewed_records field into 8 equal-width buckets and flag any outlier sessions using IQR?”
Detecting abnormal label change spikes
“Flag any days where changed_labels looks like an outlier across my 60-row label review dataset, and give me a 5-bin histogram so I can see the distribution.”
Comparing review throughput across dataset groups
“Here's my label review CSV with group-a and group-b entries across 90 rows — run a histogram with 10 bins and IQR outlier detection on the reviewed_records field so I can spot which groups are behaving abnormally.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-170?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical analysis of label review data — specifically distribution binning and outlier detection — without any external API calls or ML predictions. Ideal for ML ops teams auditing annotation pipelines, data quality engineers reviewing label change rates, or anyone needing a quick statistical snapshot of up to 200 label review records at minimal cost ($0.01 for 2 reports).
Side effects
- Rows array empty or missing required fields (row_id, date, reviewed_records, changed_labels) returns validation error
- More than 200 rows submitted exceeds max item limit
- bins value outside 1–30 range rejected
- Invalid date format (non YYYY-MM-DD) causes schema rejection
- Null values in numeric fields may affect IQR computation accuracy
- Field enum value other than reviewed_records or changed_labels rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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