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Price Basket Observations — Record Quality Audit & Numeric Interval Filter
x402
Price Basket Observations — Record Quality Audit & Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).
Audits data quality and filters by numeric interval for up to 200 rows of price basket observations (item_price, quantity_weight), returning two analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Price basket observations — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied price basket observations records (item_price, quantity_weight). 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 analytical reports: (1) a record quality audit identifying data issues such as nulls, malformed values, or out-of-range entries across the supplied rows; and (2) a numeric interval filter report showing which rows for the selected field (item_price or quantity_weight) fall within or outside the specified minimum-maximum range. No live data or external lookups are involved — all analysis is local to the submitted data.
Example use cases
Price data quality audit for retail survey
“I have 120 rows of regional price basket data collected from a retail survey — each row has a row_id, region, date, item_price, and quantity_weight. Can you audit the quality of these records and also filter out any item_price values that fall outside the range of 5 to 250?”
Flagging abnormal quantity weights in supply chain
“I need to check my quantity_weight data for anomalies — I have 80 rows of supply chain price basket observations and I want a quality audit plus a filter to show only records where quantity_weight is between 0.1 and 100.”
Cleaning economics dataset before analysis
“Before I run my economics analysis, can you audit these 200 price basket observation rows for data quality issues and filter the item_price field to only include values between 1 and 10000? I want both the audit report and the filtered interval report.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-07-008?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) dual-report check on price basket observation data — specifically when you want both a data quality audit and a numeric range filter in a single call for up to 200 rows. Prefer this over general-purpose data validation tools when your data specifically contains item_price and quantity_weight fields with region and date context, and you do not need live lookups, predictive analytics, or external data enrichment.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, region, date, item_price, or quantity_weight) causes row-level rejection
- Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error
- Specifying a minimum greater than maximum may yield an empty interval filter result
- Null values in item_price or quantity_weight are flagged in the quality audit but may not cause a call failure
- Invalid field enum value (anything other than item_price or quantity_weight) returns a schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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