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Staking Supplied Rewards — Record Quality Audit + String Normalisation + Adjacent Row Changes
x402
Staking Supplied Rewards — Record Quality Audit + String Normalisation + 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 2026-10-29).
Runs three analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 rows of staking reward/staked-units data, all processed locally without external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Staking supplied rewards — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied staking supplied rewards records (reward_units, staked_units). 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 in a single response: (1) a record quality audit flagging missing, null, or out-of-range values in reward_units and staked_units; (2) a string normalisation report highlighting inconsistencies in text fields like instrument_group; and (3) an adjacent row changes report showing row-over-row differences in the selected numeric field (reward_units or staked_units). All analysis is performed on the supplied data with no external data sources.
Example use cases
Staking reward data quality check
“I have 120 rows of daily staking reward records with instrument groups and reward_units values — can you run a record quality audit, string normalisation, and adjacent row changes analysis on them so I can spot any bad data or formatting issues?”
Detect row-over-row reward changes
“I need to find where my staked_units values changed significantly between adjacent rows in my staking dataset — can you run the adjacent row changes report on these 80 records and focus on the staked_units field?”
Normalise instrument group strings in staking data
“My staking reward records have inconsistent instrument_group labels across 150 rows — can you run the string normalisation report on this data so I can see which entries need cleaning?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-15-200?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular staking reward records (up to 200 rows) and need three complementary data-quality perspectives in a single call at minimal cost ($0.01 USDC). It is ideal for offline/local analysis of supplied data without any external API calls, live price lookups, or predictions. Prefer it over single-report endpoints when you need quality audit, string normalisation, and adjacent-row change detection simultaneously on the same dataset.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, instrument_group, date, reward_units, staked_units) causes rejection
- Invalid date format (not YYYY-MM-DD) triggers a schema validation error
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array (minItems:1 not met) causes a bad request error
- Payment failure via x402 protocol blocks the request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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