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Competitor Supplied Prices — Record Quality Audit + String Normalisation + Base-100 Series
x402
Competitor Supplied Prices — Record Quality Audit + String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Runs three analytical reports (record quality audit, string normalisation, and base-100 rebase series) on up to 200 rows of competitor-supplied price data (list_price, package_quantity) using local engines with no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Competitor supplied prices — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series for supplied competitor supplied prices records (list_price, package_quantity). 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
Three independent analytical reports delivered together: (1) a record quality audit flagging malformed, missing, or suspicious entries across the supplied rows; (2) a string normalisation report identifying and standardising inconsistent string values in company_group and date fields; and (3) a base-100 rebase series for the selected numeric field (list_price or package_quantity) anchored at the specified base row index. All computed locally with no external data lookups.
Example use cases
Competitor pricing data quality check
“I've collected 120 rows of competitor pricing data with list_price and package_quantity fields — can you run a record quality audit on them, normalise any string issues, and produce a base-100 series indexed from the first row using list_price?”
Retail price index benchmarking
“I need to rebase our competitor's package_quantity data to a base-100 series starting at row index 5, and also check the dataset for record quality problems and string formatting issues — there are about 80 rows total.”
Supply chain price dataset validation
“Before we import these 200 competitor price records into our dashboard, can you run the three-report suite — record quality audit, string normalisation, and base-100 rebase — on the list_price field so we can catch any bad data first?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-07-201?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a batch of competitor pricing records (up to 200 rows) and need all three of: a data quality audit, string normalisation, and a base-100 index series in a single paid call. It is more cost-effective than calling separate single-report endpoints. Prefer it over generic data quality tools when your data specifically involves list_price and package_quantity fields from competitor sources and you want competitive pricing analytics rather than general-purpose ETL.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum batch size
- base_index out of range for the supplied row count — validation error
- Invalid date format in rows (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside allowed range (-1T to +1T) — schema rejection
- Missing required fields (row_id, company_group, date, list_price, package_quantity) — validation error
- Payment of 0.01 USDC not included or invalid — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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