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Staking Rewards — Record Quality Audit + String Normalisation + Keyed Dataset Comparison
x402
Staking Rewards — 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 on staking reward records: a data quality audit, string normalisation, and a keyed comparison between two supplied datasets (up to 200 rows each).
Price / call$0.01
Success—
StatusUnknown
How this service works
Staking supplied rewards — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison 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
Returns three independent analytical reports: (1) a record quality audit flagging nulls, out-of-range values, and structural issues in the staking records; (2) a string normalisation report showing standardised versions of text fields like instrument_group; and (3) a keyed dataset comparison report identifying row-level differences in reward_units and staked_units between the two supplied datasets, all computed locally without external lookups.
Example use cases
Pre-import staking data validation
“Before I load these staking reward records into our database, can you run a record quality audit and string normalisation on the dataset? It has about 50 rows covering instrument groups eth-main and sol-main from 2026-01-01 to 2026-02-19, with reward_units and staked_units for each day.”
Reconcile two reward dataset versions
“I have two exports of our staking rewards data — the original and a corrected version — both with the same row IDs. Can you do a keyed comparison to tell me exactly which rows changed in reward_units or staked_units, and also flag any data quality issues?”
Detect formatting issues in instrument group labels
“Our staking data pipeline sometimes produces inconsistent instrument_group labels like 'ETH-Main', 'eth main', and 'ETH_MAIN'. Can you run a string normalisation report on our 120-row reward dataset dated from 2025-06-01 to 2025-09-28 so we can see what needs cleaning?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-15-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined analytical passes — quality audit, string normalisation, and keyed comparison — on staking reward data (reward_units, staked_units) in a single low-cost call. It is best suited for offline/batch validation of supplied datasets rather than live data lookups or predictive analysis. Prefer it over single-report endpoints when you need all three reports for the same staking dataset at once.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, instrument_group, date, reward_units, staked_units) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejection
- Empty rows array (minItems: 1 not met) — error
- Payment of 0.01 USDC not included — 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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