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Transaction Fee Observations — Record Quality Audit + String Normalisation + Numeric Interval Filter
x402
Transaction Fee Observations — Record Quality Audit + String Normalisation + Numeric Interval Filter 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).
Audits record quality, normalises strings, and filters by numeric interval for up to 200 transaction fee observation rows, returning 3 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transaction fee observations — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied transaction fee observations records (fee_units, transaction_count). 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: (1) a record quality audit identifying issues such as missing, null, or malformed values across the supplied rows; (2) a string normalisation report for the instrument_group and date string fields; (3) a numeric interval filter report showing which rows fall within the specified minimum–maximum range for the chosen field (fee_units or transaction_count). All analysis is performed locally with no external lookups or predictions.
Example use cases
Fee data quality check before reporting
“I need to audit the quality of my transaction fee records before generating the monthly report. Can you check these 80 rows for data quality issues, normalise the instrument_group strings, and filter the fee_units field to only include values between 0 and 10000?”
Detecting out-of-range transaction counts
“Can you run a numeric interval filter on transaction_count for my 120 fee observation rows, keeping only records where transaction_count falls between 1 and 5000, and also give me a record quality audit on the whole dataset?”
Cleaning instrument group labels in fee data
“My transaction fee dataset has messy instrument_group strings and I suspect some duplicates or formatting issues. Can you run string normalisation and a record quality audit on these 30 rows, and also filter fee_units between 5 and 250?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-03-197?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 transaction fee observation rows and need all three of record quality auditing, string normalisation, and numeric interval filtering in a single call at low cost ($0.01 USDC). It is ideal for pre-reporting data hygiene checks on fee and transaction count data without needing live lookups, predictions, or external data sources. Prefer alternatives if you need more than 200 rows, real-time enrichment, forecasting, or professional financial assessment.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Invalid date format in date field (must match YYYY-MM-DD pattern)
- Numeric values outside allowed range (-1e12 to 1e12) cause validation errors
- Missing required fields (row_id, instrument_group, date, fee_units, transaction_count) cause schema errors
- minimum greater than maximum causes undefined filter behaviour
- Payment not provided or insufficient USDC causes 402 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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