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Asset Coverage Record Quality Audit + String Normalisation + Keyed Dataset Comparison
x402
Asset Coverage 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 2026-10-24).
Runs three local analytical reports on supplied asset coverage records: record quality audit, string normalisation, and keyed dataset comparison between known_assets and monitored_assets datasets (up to 200 rows).
Price / call$0.01
Success—
StatusUnknown
How this service works
Asset coverage — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison for supplied asset coverage records (known_assets, monitored_assets). 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: (1) a record quality audit flagging missing, null, or malformed values across the supplied rows; (2) a string normalisation report cleaning and standardising string fields such as control_group and row_id; (3) a keyed dataset comparison report highlighting differences between known_assets and monitored_assets values on matching keys. All computed locally with no external lookups.
Example use cases
Detecting gaps in monitored asset coverage
“I have two sets of asset coverage data — known_assets and monitored_assets — across about 80 rows by date and control group. Can you audit the record quality, normalise any string inconsistencies, and compare the two datasets by key to find where monitored assets don't match what we expect?”
Data quality check before financial reporting
“Before I submit our quarterly asset coverage report, can you run a quality audit and string normalisation pass on our records, plus a keyed comparison between the known and monitored asset figures? I've got around 120 rows with dates, control groups, and both asset columns.”
Validating control group asset data integrity
“We've got asset coverage records for three control groups over the past month — about 90 rows total. Run the record quality audit, string normalisation, and keyed dataset comparison so I can see where there are data issues or mismatches between known_assets and monitored_assets.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-security-10-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three distinct data quality operations — record quality audit, string normalisation, and keyed dataset comparison — on asset coverage data in a single cost-efficient call. It is ideal when you have up to 200 rows of known_assets and monitored_assets records and want offline, local analytics without any live data lookup or external enrichment. Prefer it over separate single-report endpoints when all three analyses are needed simultaneously to save cost and round-trips.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, control_group, date, known_assets, monitored_assets) cause validation errors
- Date fields not matching YYYY-MM-DD pattern cause schema rejection
- Numeric values outside ±1,000,000,000,000 range rejected
- Empty rows array rejected (minItems: 1)
- Payment not included or insufficient USDC causes 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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