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Transaction Fee Observations — Daily Sum Series + Adjacent Row Changes
x402
Transaction Fee Observations — Daily Sum Series + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Computes a daily sum time series and adjacent row-to-row change report for supplied transaction fee observation records (fee_units or transaction_count).
Price / call$0.01
Success—
StatusUnknown
How this service works
Transaction fee observations — Daily sum series + Adjacent row changes: Daily sum series + Adjacent row changes for supplied transaction fee observations records (fee_units, transaction_count). 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
Returns two analytical reports: (1) a daily sum series aggregating the chosen field (fee_units or transaction_count) by date, and (2) an adjacent row change report showing the difference between consecutive observations. Up to 200 input rows supported per call.
Example use cases
Daily fee revenue trend analysis
“I have a week of transaction fee records with date, fee_units, and transaction_count — can you compute the daily total fee_units and show me how fees changed between consecutive days?”
Instrument group fee aggregation
“I need a daily sum series for fee_units across my instrument groups (group-a and group-b) plus the day-over-day differences. Here are my 10 rows of transaction data with dates from 2026-10-01 to 2026-10-10.”
Transaction count daily rollup
“Can you aggregate my transaction_count field into a daily sum series and flag the changes between each adjacent row? I have about 50 records across different instrument groups that I want summarized.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-03-137?utm_source=zero.xyzWhen to prefer
Use this endpoint when you have raw transaction fee observation records and need both a daily aggregated sum time series and a consecutive-row delta report in a single call. It is ideal for offline/batch analytical workflows where you supply your own data (no live data fetched) and need two complementary reports cheaply. Prefer this over general-purpose analytics tools when working with the specific fee_units/transaction_count schema and needing deterministic local computation.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, instrument_group, fee_units, transaction_count) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — schema validation failure
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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