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Business Location Inventories — Record Quality Audit + String Normalisation + Trailing Mean Series
x402
Business Location Inventories — Record Quality Audit + String Normalisation + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Runs three offline analytical reports on business location inventory data: record quality audit, string normalisation, and trailing mean series computation (up to 200 rows).
Price / call$0.01
Success—
StatusUnknown
How this service works
Business location inventories — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series for supplied business location inventories records (location_count, verified_locations). 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 for the supplied rows: (1) a record quality audit flagging issues like nulls, out-of-range values, and malformed records; (2) a string normalisation report showing standardised forms of text fields like company_group; (3) a trailing mean series for the selected numeric field (location_count or verified_locations) computed with the specified window size — all processed offline using local analytical engines without external lookups.
Example use cases
Monthly location data health check
“I have 150 rows of monthly business location inventory records with location_count and verified_locations. Can you run the record quality audit, string normalisation, and a trailing mean with window size 6 on location_count to see how data quality looks?”
Spotting inconsistent company name formatting
“My location dataset has company_group strings like 'Corp A', 'corp a', and 'CORP A' mixed in. Run the string normalisation report plus the record quality audit on these rows so I can see what needs cleaning — here's the data with verified_locations as the metric field.”
Trend smoothing for verified location counts
“Can you compute a trailing mean series with a window of 3 for verified_locations across my 80 rows of franchise location data, along with the usual record quality and string normalisation reports?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-05-199?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled offline data-quality reports — record audit, string normalisation, and trailing mean — on a small-to-medium batch of business location inventory rows (up to 200) without needing live lookup, external enrichment, or predictions. It is cost-effective at $0.01 for all three reports and ideal for automated pipeline checks on location_count and verified_locations metrics.
Side effects
- Fewer than 1 or more than 200 rows supplied — request rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, date, company_group, location_count, verified_locations) causes row rejection
- Window size less than 2 or greater than 200 causes validation error
- Numeric values outside ±1,000,000,000,000 are rejected
- Payment of 0.01 USDC not supplied — 402 response returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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