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Feature Availability Duplicate Key Report + IQR Outlier Flags
x402
Feature Availability 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 2026-10-20).
Analyzes up to 200 feature availability records to produce a duplicate key report and IQR-based outlier flags for populated_features or expected_features values.
Price / call$0.01
Success—
StatusUnknown
How this service works
Feature availability — Duplicate key report + IQR outlier flags: Duplicate key report + IQR outlier flags for supplied feature availability records (populated_features, expected_features). 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 any row_ids that appear more than once across the submitted records, and (2) IQR outlier flags marking rows where the selected field (populated_features or expected_features) falls beyond 1.5 times the interquartile range. Results are computed locally with no external lookups and cover up to 200 submitted rows.
Example use cases
ML pipeline feature coverage audit
“I have a batch of 50 feature availability records from my ML pipeline and want to know if any row IDs are duplicated and if any populated_features counts are statistical outliers — can you run the duplicate key report and IQR flag analysis on them?”
Data ingestion quality gate
“Before I load this dataset into our feature store, check these 120 feature availability rows for duplicate row IDs and flag any expected_features values that fall outside 1.5 times the interquartile range so I can investigate before ingestion.”
Daily feature monitoring anomaly check
“Run a duplicate key and IQR outlier check on today's feature availability snapshot — I have 80 rows with row_id, dataset_group, date, populated_features, and expected_features, and I want to analyze the populated_features column for anomalies.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-10-065?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical data quality checks on feature availability records specifically — combining duplicate key detection and IQR outlier flagging in a single low-cost call. Ideal for pre-ingestion validation, pipeline quality gates, or batch auditing of up to 200 rows where no external enrichment or prediction is needed.
Side effects
- Submitting more than 200 rows returns an error — batch must be split
- Missing required fields (row_id, date, populated_features, expected_features) cause validation failure
- Invalid date format (non-YYYY-MM-DD) triggers schema rejection
- Fewer than 4 rows may produce unreliable IQR statistics
- Null values in the selected analysis field may be excluded from outlier computation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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