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Simulation Caches — Record Quality Audit + String Normalisation + Grouped Numeric Summary
x402
Simulation Caches — Record Quality Audit + String Normalisation + Grouped Numeric Summary 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).
Runs three local analytical reports on simulation cache records: a data quality audit, string normalisation, and grouped numeric summary — all in one call for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary 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: (1) a record quality audit flagging data issues such as nulls, out-of-range values, or malformed dates; (2) a string normalisation report cleaning and standardising text fields like asset_group; and (3) a grouped numeric summary aggregating cache_gb or simulation_seconds by category. All computed locally without external lookups.
Example use cases
Simulation cache data quality check
“I have a batch of simulation cache records with cache_gb and simulation_seconds values — can you audit them for quality issues, normalise the string fields, and give me a grouped numeric summary broken down by asset_group? Here are 50 rows.”
Grouped summary of cache sizes
“Can you analyse these 120 simulation cache rows and give me a grouped numeric summary of cache_gb by asset group, along with a quality audit and string normalisation report?”
Pre-pipeline data validation for sim records
“Before I load these simulation cache records into our pipeline, can you run a quality audit and string normalisation pass on all 200 rows, and also summarise simulation_seconds by group so I can spot anomalies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-194?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three combined analytical operations — quality auditing, string normalisation, and grouped numeric summarisation — on simulation cache data (cache_gb, simulation_seconds) in a single cost-efficient call. Ideal when you want offline, local computation without any external lookups, predictions, or live data dependencies, and your dataset fits within 200 rows.
Side effects
- Exceeding 200 rows returns an error or truncation
- Missing required fields (row_id, asset_group, date, cache_gb, simulation_seconds) cause validation failure
- Malformed date strings not matching YYYY-MM-DD pattern may be flagged or rejected
- Numeric values outside the allowed range trigger schema validation errors
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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