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Simulation Caches — Record Quality Audit + String Normalisation + Numeric Interval Filter
x402
Simulation Caches — Record Quality Audit + String Normalisation + Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).
Audits record quality, normalises strings, and filters by numeric interval for up to 200 simulation cache records (cache_gb, simulation_seconds) in three independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied simulation caches records (cache_gb, simulation_seconds). 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 for the supplied simulation cache rows: (1) a record quality audit identifying issues like missing or malformed values; (2) a string normalisation report for fields such as asset_group and date; and (3) a numeric interval filter report identifying which rows fall within or outside the specified minimum/maximum bounds for the selected numeric field (cache_gb or simulation_seconds). All analysis is performed locally with no external lookups or live data.
Example use cases
Validating simulation cache data before pipeline ingestion
“I have 120 simulation cache records with cache_gb and simulation_seconds columns and I need to check them for quality issues, normalise the asset_group strings, and filter out any cache_gb values outside the range 5 to 500 before I load them into my pipeline.”
Identifying out-of-range simulation durations
“Can you audit my simulation cache dataset for record quality problems, normalise the text fields, and flag any rows where simulation_seconds falls outside 0 to 3600? I have 80 rows total.”
Cleaning asset group names in cache records
“I need to normalise the string fields in my simulation cache data — there are about 30 rows with asset_group names that need cleaning — and also run a quality audit and a numeric interval filter on cache_gb between 10 and 200.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-197?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have simulation cache records with cache_gb and/or simulation_seconds numeric fields and need three combined analytical operations — quality audit, string normalisation, and numeric interval filtering — in a single low-cost call (up to 200 rows, $0.01 USDC). It is ideal for data engineering pre-processing workflows where you want to validate, clean, and filter simulation data without any external API calls or live predictions.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, asset_group, date, cache_gb, simulation_seconds) causes row-level rejection
- Invalid date format (non-YYYY-MM-DD) triggers schema validation failure
- Minimum greater than maximum for interval filter may produce empty filter results or an error
- Numeric values outside the allowed range (-1e12 to 1e12) are rejected by schema validation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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