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Transaction Fee Observations — Record Quality Audit + String Normalisation + Numeric Distribution
x402
Transaction Fee Observations — Record Quality Audit + String Normalisation + Numeric Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).
Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of transaction fee observation data containing fee_units and transaction_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transaction fee observations — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution 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
Returns three independent reports: (1) a record quality audit detailing completeness, missing values, and structural issues across all rows; (2) a string normalisation report covering the instrument_group and other string fields; and (3) a numeric distribution summary (e.g. min, max, mean, percentiles) for the selected numeric field (fee_units or transaction_count). All analysis is performed locally on the supplied data with no external lookups.
Example use cases
Pre-ingestion data quality check
“Before I load these transaction fee records into our data warehouse, can you run a full quality audit and string normalisation check on these 150 rows of fee observations — each row has a row_id, instrument_group, date, fee_units, and transaction_count — so I can catch any issues first?”
Fee distribution analysis by instrument group
“I have 80 rows of transaction fee observations broken down by instrument group and date. Can you give me a numeric distribution report on the transaction_count field so I can see how fees are spread across the dataset?”
Data cleanliness review for finance reporting
“I need to audit these 200 transaction fee records for data quality issues and check that all the string fields like instrument_group are properly normalised before we send them to the finance team — can you run all three reports on the fee_units field?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-03-193?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a batch of transaction fee observation records (up to 200 rows) and need three simultaneous data quality reports — quality audit, string normalisation, and numeric distribution — in a single low-cost call. Prefer this over general-purpose data tools when your data specifically contains fee_units and transaction_count fields with instrument_group categorisation. It is ideal for pre-ingestion validation, finance data pipeline checks, or quick profiling of fee datasets without requiring any external data sources or live lookups.
Side effects
- Rows array is empty or missing — minimum 1 row required
- More than 200 rows submitted — exceeds maximum batch size
- Invalid date format in any row — must match YYYY-MM-DD pattern
- row_id missing or blank — required per row
- Numeric fields (fee_units, transaction_count) out of allowed range (±1,000,000,000,000)
- Invalid field selector — must be either 'fee_units' or 'transaction_count'
- Payment not included or incorrect — $0.01 USDC required per call
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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