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Transaction Fee Observations — Record Quality Audit + String Normalisation + Keyed Dataset Comparison
x402
Transaction Fee Observations — Record Quality Audit + String Normalisation + Keyed Dataset Comparison 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).
Runs three local analytical reports (record quality audit, string normalisation, and keyed dataset comparison) on up to 200 rows of transaction fee observation data (fee_units, transaction_count).
Price / call$0.01
Success—
StatusUnknown
How this service works
Transaction fee observations — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison 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 returned together: (1) a record quality audit flagging missing, null, or out-of-range values across fee_units and transaction_count fields; (2) a string normalisation report showing standardised versions of text fields like instrument_group; (3) a keyed dataset comparison report highlighting rows where the two supplied datasets differ by key (row_id). All analysis is performed locally on the supplied data — no external lookups or predictions.
Example use cases
Pre-load data quality check for fee records
“Before I load these 150 transaction fee rows into my data warehouse, can you run a record quality audit and string normalisation on them to catch any bad values or inconsistent instrument_group names? Here are the rows with date, row_id, fee_units, and transaction_count.”
Reconciling two fee datasets by key
“I have two extracts of transaction fee observations for October 2026 — one from our trading system and one from the settlement system — both with the same row IDs. Can you do a keyed dataset comparison to show me where fee_units or transaction_count differ between them?”
Cleaning instrument group labels in fee data
“My transaction fee dataset has messy instrument_group strings with mixed casing and whitespace — can you run a string normalisation report on these 80 rows so I can see what gets cleaned up before I use them for reporting?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-03-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three specific analytical operations — record quality audit, string normalisation, and keyed dataset comparison — applied together to transaction fee observations (fee_units, transaction_count) in a single call for $0.01. Prefer it over building your own pipeline when you need a quick, cheap, offline-safe data QA pass on up to 200 rows without sending data to a live prediction or external enrichment service.
Side effects
- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — request rejected with max items error
- Row missing required fields (row_id, instrument_group, date, fee_units, transaction_count) — schema validation error
- Date field does not match YYYY-MM-DD pattern — schema validation error
- fee_units or transaction_count outside allowed numeric range — schema validation error
- row_id exceeds 80 characters — schema validation error
- Payment of 0.01 USDC not provided or rejected — 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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