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Simulation Caches — Record Quality Audit + Equal-Width Histogram
x402
Simulation Caches — Record Quality Audit + Equal-Width Histogram 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 and generates an equal-width histogram for simulation cache data (cache_gb and simulation_seconds fields) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Record quality audit + Equal-width histogram: Record quality audit + Equal-width histogram for supplied simulation caches records (cache_gb, simulation_seconds). 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 record quality audit identifying missing, null, or out-of-range values across the supplied rows, and (2) an equal-width histogram for the selected numeric field (cache_gb or simulation_seconds) divided into the specified number of bins, showing frequency counts per bin.
Example use cases
Cache size distribution audit
“I have 50 simulation cache records with cache_gb and simulation_seconds values across two asset groups — can you audit their data quality and show me a 5-bin histogram of the cache_gb distribution so I can spot outliers?”
Simulation duration quality check
“Please check my simulation records for quality issues and build an equal-width histogram with 8 bins on the simulation_seconds field — I want to understand how run times are distributed across my dataset.”
Asset group cache analytics
“I need a quality audit and a 10-bin histogram for about 120 simulation cache records across multiple asset groups, focusing on the cache_gb field — can you run both reports at once?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-013?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need simultaneous data quality auditing and distribution analysis specifically for simulation cache records (cache_gb, simulation_seconds) in a single low-cost call. It is ideal for datasets up to 200 rows where you want both a completeness/validity check and a histogram without setting up a local analytics pipeline. Prefer it over generic data tools when your data is already structured in the expected simulation cache schema.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, cache_gb, simulation_seconds) causes rejection
- Invalid date format (non-YYYY-MM-DD) triggers schema validation failure
- bins value outside 1–30 range is rejected
- Supplying all-null values for the selected field may produce an empty or degenerate histogram
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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