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Simulation Caches — Record Quality Audit + String Normalisation
x402
Simulation Caches — Record Quality Audit + String Normalisation 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 data quality and normalises strings for simulation cache records (cache_gb, simulation_seconds) across up to 200 rows, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Record quality audit + String normalisation: Record quality audit + String normalisation 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
Two independent analytical reports: (1) a record quality audit identifying data issues such as missing values, out-of-range numbers, type errors, or anomalies in cache_gb and simulation_seconds fields; (2) a string normalisation report for text fields like asset_group, flagging and correcting inconsistent casing, whitespace, or formatting. Both reports are generated from the supplied data with no external lookups.
Example use cases
Simulation pipeline data hygiene check
“I have a batch of simulation cache records from last month with asset_group labels like 'Group A', 'group-a', and 'GROUP A' — can you audit the data quality and normalise those strings so everything is consistent? Here are the rows with their cache_gb and simulation_seconds values.”
Flagging bad values in cache size data
“Some of my simulation cache records look suspicious — a few cache_gb values seem way off and some simulation_seconds entries might be null or negative. Can you run a quality audit on these 150 rows and tell me what's wrong?”
Preparing simulation data for downstream reporting
“Before I hand off this simulation cache dataset to my reporting team, I need a quality audit and string normalisation pass on the asset_group column. Can you process these records — they span dates from 2026-10-01 to 2026-10-31 with cache_gb and simulation_seconds fields — and give me the two reports?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-001?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously audit the data quality of simulation cache records and normalise string fields in a single API call for up to 200 rows. It is ideal for data engineering pipelines that process simulation performance data (cache size and duration) and need both a quality gate and string standardisation before downstream use. Prefer this over generic data quality tools when your domain is specifically simulation cache metrics with the cache_gb and simulation_seconds schema.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, cache_gb, simulation_seconds, asset_group) cause row-level rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside allowed range cause schema rejection
- Empty rows array returns an error
- Payment failure via x402 protocol prevents processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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