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Simulation Caches — Record Quality Audit + String Normalisation + Daily Sum Series
x402
Simulation Caches — Record Quality Audit + String Normalisation + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).
Runs three local analytical reports on simulation cache records: record quality audit, string normalisation, and daily sum series aggregation — up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series 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 submitted rows: (1) a record quality audit flagging data issues such as nulls or out-of-range values, (2) a string normalisation report cleaning the asset_group text field, and (3) a daily sum series aggregating the chosen numeric field (cache_gb or simulation_seconds) by date. All processing is local with no external lookups.
Example use cases
Daily cache usage totals by date
“I have a list of simulation cache records with dates, asset groups, and cache_gb values — can you generate a daily sum series so I can see total cache usage per day? Use cache_gb as the field and here are my rows: row-1 on 2026-10-01, group-a, 10 GB; row-2 on 2026-10-02, group-b, 20 GB; row-3 on 2026-10-03, group-a, 15 GB.”
Audit simulation record data quality
“Can you run a record quality audit on these simulation cache records to flag any missing values, out-of-range numbers, or malformed dates? I've got about 50 rows with row_id, asset_group, date, cache_gb, and simulation_seconds fields.”
Normalise asset group labels across simulation data
“My simulation cache dataset has inconsistent asset group names — things like 'Group A', 'group-a', and 'GROUP_A' all meaning the same thing. Can you run the string normalisation report on my rows so I get a clean, consistent version of each asset_group label?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-198?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three specific analytical operations — quality audit, string normalisation, and daily sum series — performed together on simulation cache data (cache_gb, simulation_seconds) in a single cost-effective call. It is ideal for batch sizes up to 200 rows where no live external data, predictions, or professional assessments are required, and all computation is self-contained.
Side effects
- More than 200 rows submitted — endpoint rejects or truncates input
- Invalid date format (not YYYY-MM-DD) causes row-level errors
- Missing required fields (row_id, asset_group, date) causes validation failure
- Invalid field enum value (not 'cache_gb' or 'simulation_seconds') causes request rejection
- Empty rows array returns an error
- Payment of 0.01 USDC not included or declined results in 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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