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Trade Observations Data Quality & Analytics Suite
x402
Trade Observations Data Quality & Analytics Suite is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Runs three analytics reports on trade observation records: a record quality audit, string normalization, and a date-by-category pivot — all applied to export_amount and import_amount fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Trade observations — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied trade observations records (export_amount, import_amount). 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
Returns three independent reports based on the submitted trade observation rows: (1) a record quality audit flagging missing, null, or out-of-range values in export_amount and import_amount; (2) a string normalization report standardizing region field values; and (3) a date-by-category pivot table summarizing the selected field (export_amount or import_amount) broken down by date and region category. All computed locally without external lookups.
Example use cases
Export data quality review
“I have a batch of 50 trade observation rows with region names and export/import amounts — can you run a record quality audit, normalize the region strings, and pivot export_amount by date and region category so I can spot issues?”
Import amount pivot by region
“Take these trade records across group-a and group-b regions from October 2026 and give me a date-by-category pivot on import_amount, plus flag any string inconsistencies in the region field.”
Trade dataset onboarding validation
“Before we load this new trade dataset into our pipeline, can you audit all 120 rows for record quality problems, normalize any messy region strings, and produce a pivot of export_amount grouped by date and category?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-06-206?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously audit data quality, normalize categorical string fields, and generate a time-series pivot from trade observation data in a single low-cost call. It is well-suited for economics pipelines that need to validate and summarize import/export records before downstream processing, and works entirely on supplied data without any live market lookups or external API calls.
Side effects
- Rows array empty or missing — validation error returned
- More than 200 rows submitted — request rejected with size limit error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- row_id missing or empty string — required field validation error
- Field enum value not 'export_amount' or 'import_amount' — rejected
- export_amount or import_amount outside ±1,000,000,000,000 — validation error
- Payment of 0.01 USDC not provided — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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