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Price Basket Observations — Record Quality Audit + Category Frequencies
x402
Price Basket Observations — Record Quality Audit + Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs a record quality audit and category frequency analysis on up to 200 price basket observation rows (item_price, quantity_weight), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Price basket observations — Record quality audit + Category frequencies: Record quality audit + Category frequencies 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 independent analytical reports: (1) a record quality audit detailing completeness, validity, and data issues per row across item_price and quantity_weight fields; and (2) a category frequency report showing how often each distinct category value (e.g. region, date) appears across the supplied rows. Both reports are computed locally with no external lookups.
Example use cases
Retail pricing data quality check
“I have 150 rows of store price observations with item_price and quantity_weight fields — can you run a quality audit to flag any nulls, out-of-range values, or malformed dates, and also show me how frequently each region appears in the dataset?”
Economics dataset validation before analysis
“Before I run my regression, can you audit these 80 price basket records for data quality issues and give me a frequency count of each category like region and date so I can spot imbalances?”
Basket survey response review
“We collected 200 basket survey responses with item prices and weights across group-a and group-b regions — can you check the record quality and tell me how often each region and date shows up in the data?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-07-006?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular price basket observation data (with item_price and quantity_weight fields) and need both a data quality audit and category frequency summary in a single $0.01 call. It is ideal for pre-analysis validation of economics or retail datasets of up to 200 rows where no live lookup, external enrichment, or prediction is needed — purely local analytical computation.
Side effects
- Input array is empty (minItems:1 not met) — validation error
- More than 200 rows submitted — request rejected (maxItems:200)
- Missing required fields (row_id, region, date, item_price, quantity_weight) on any row — validation error
- Date field does not match YYYY-MM-DD format — pattern validation failure
- item_price or quantity_weight outside allowed numeric range — rejected
- Payment of 0.01 USDC not fulfilled — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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