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Sampling Observations — Record Quality Audit + Exact Row Deduplication + IQR Outlier Flags
x402
Sampling Observations — Record Quality Audit + Exact Row Deduplication + 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 three local analytical reports on up to 200 sampling observation rows: a record quality audit, exact row deduplication, and IQR-based outlier detection for sample_value or sample_weight.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Record quality audit + Exact row deduplication + IQR outlier flags: Record quality audit + Exact row deduplication + IQR outlier flags for supplied sampling observations records (sample_value, sample_weight). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports: (1) a record quality audit identifying missing, malformed, or invalid field values; (2) an exact row deduplication report listing duplicate records; and (3) IQR-based outlier flags for the selected numeric field (sample_value or sample_weight). All reports are computed locally with no external lookups.
Example use cases
Pre-analysis data quality check
“Before I run my analysis, can you check these 80 sampling observation rows for record quality problems, exact duplicates, and IQR outliers on the sample_value field? I want all three reports at once.”
Detecting outlier sample weights
“I need to find outlier rows based on IQR in the sample_weight field across my 120 grouped observations — also flag any quality issues or exact duplicate records while you're at it.”
Deduplication audit for merged datasets
“I've merged two datasets of sampling observations and I'm worried there are duplicate rows — can you run the exact deduplication report along with the quality audit and IQR outlier check on sample_value for these 200 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-220?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three simultaneous data quality reports (quality audit, deduplication, and IQR outlier detection) on sampling observation records in a single low-cost call. Ideal for pre-analysis data cleaning pipelines where sample_value and sample_weight are the key numeric fields. Best suited for datasets under 200 rows that require offline, deterministic analysis with no external data lookups or predictions.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) causes schema rejection
- Invalid date format (non-YYYY-MM-DD) fails pattern validation
- Numeric values outside [-1e12, 1e12] range are rejected
- Empty rows array is rejected (minItems: 1)
- Invalid field enum value (anything other than sample_value or sample_weight) causes error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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