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Trade Observations Record Quality Audit and String Normalisation
x402
Trade Observations Record Quality Audit and String Normalisation 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).
Audits trade observation records (export_amount, import_amount) for data quality issues and normalises strings, producing two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Trade observations — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied trade observations records (export_amount, import_amount). 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
Two independent analytical reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, malformed dates, and inconsistencies in the trade observation fields; and (2) a string normalisation report showing how region and other string fields have been standardised. Both reports cover up to 200 input rows and are computed locally without any external lookups.
Example use cases
Pre-pipeline trade data validation
“Before I load this batch of trade records into our data warehouse, can you audit them for quality issues and normalise the string fields? I have about 50 rows with region, date, export_amount, and import_amount columns.”
Detecting bad values in export import figures
“I've got a trade observations dataset with 120 rows and I'm seeing some weird numbers in the export_amount and import_amount columns. Can you run a record quality audit on them and also normalise the region strings?”
Monthly trade data QA before reporting
“We generate a monthly trade report and I need to quality-check this month's 80 observation rows — covering region, date, export_amount, and import_amount — before we publish. Can you audit the records and normalise any inconsistent strings?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-06-001?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need simultaneous record quality auditing and string normalisation specifically for trade observation data containing export_amount and import_amount fields, and you want two separate reports in a single low-cost call. It is best suited for batch sizes up to 200 rows where no live lookup, prediction, or external data enrichment is needed — purely local analytical processing of supplied data.
Side effects
- Payload exceeds 200 rows — endpoint rejects with validation error
- Missing required fields (row_id, region, date, export_amount, import_amount) cause row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern may trigger schema validation failure
- Numeric values outside ±1,000,000,000,000 range are rejected by schema
- Empty rows array (minItems:1 violated) returns error
- Payment of 0.01 USDC not provided or x402 protocol failure blocks request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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