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Simulation Caches — Numeric Interval Filter + Two-Measure Correlation
x402
Simulation Caches — Numeric Interval Filter + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).
Filters simulation cache records by a numeric interval on one field and computes the correlation between cache_gb and simulation_seconds across up to 200 supplied rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Numeric interval filter + Two-measure correlation: Numeric interval filter + Two-measure correlation 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 numeric interval filter report listing which rows from the supplied dataset fall within the specified [minimum, maximum] range on the chosen field (cache_gb or simulation_seconds), and (2) a two-measure correlation report quantifying the statistical relationship between cache_gb and simulation_seconds across the supplied records. Up to 200 rows are processed; no external data or predictions are involved.
Example use cases
Simulation performance correlation audit
“I have my simulation cache logs for October — 120 rows with asset_group, date, cache_gb, and simulation_seconds. Filter to records where cache_gb is between 10 and 100, then tell me if there's a meaningful correlation between cache size and how long simulations ran.”
Identify cache efficiency range for a workload
“Can you take my 80 simulation cache records, filter to only those where simulation_seconds is between 30 and 300 seconds, and then compute the correlation between cache_gb and simulation_seconds so I can see if bigger caches actually speed things up?”
Asset group cache analysis before capacity planning
“Here are 200 rows of simulation cache data across multiple asset groups. I want to filter to entries where cache_gb falls between 20 and 500, then run a two-measure correlation between cache_gb and simulation_seconds so I can decide how to size our cache for the next quarter.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-131?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have simulation cache records with both a cache_gb and simulation_seconds field and need two simultaneous analytical outputs: a numeric range filter and a correlation between those two measures. It is ideal for small-to-medium batch analysis (up to 200 rows) of your own supplied data without requiring any external data lookup or live computation infrastructure. Prefer it over general-purpose analytics tools when you want a cost-effective ($0.01 USDC), self-contained dual-report on simulation performance data.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required row fields (row_id, date, cache_gb, simulation_seconds, asset_group) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Field enum value not recognized (must be cache_gb or simulation_seconds) — error response
- All values in the selected field are null — correlation or filter computation may return empty or undefined result
- minimum greater than maximum — filter returns zero rows
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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