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Simulation Caches Duplicate Key Report + Trailing Mean Series
x402
Simulation Caches Duplicate Key Report + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).
Generates two local analytical reports for simulation cache data: a duplicate key report and a trailing mean series for cache_gb or simulation_seconds fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Duplicate key report + Trailing mean series: Duplicate key report + Trailing mean series 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 independent analytical reports: (1) a duplicate key report identifying rows with repeated keys across the supplied simulation cache records, and (2) a trailing mean series (rolling average) over the chosen numeric field (cache_gb or simulation_seconds) using the specified window size. Up to 200 rows supported per call.
Example use cases
Duplicate detection in simulation logs
“I have 50 rows of simulation cache records with row IDs, asset groups, dates, cache_gb and simulation_seconds — can you run a duplicate key report to find any rows with repeated identifiers? Here's the data.”
Rolling average of cache storage over time
“Take these 30 simulation cache entries and compute a trailing mean series with a window of 5 for the cache_gb field so I can see the smoothed storage trend over time.”
Data quality audit before pipeline ingestion
“Before I ingest these simulation cache records into our pipeline, run both a duplicate key check and a trailing mean analysis with window 4 on simulation_seconds — flag anything that looks off.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-061?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have simulation cache tabular data (with cache_gb and simulation_seconds columns) and need both a duplicate key audit and a rolling mean trend analysis in a single low-cost call. It is well-suited for data quality checks before pipeline ingestion or for lightweight local analytics without external data lookups or live computations.
Side effects
- Input array is empty or exceeds 200 rows — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- window value less than 2 or greater than 200 — rejected
- field value not in enum ['cache_gb','simulation_seconds'] — rejected
- Missing required row fields (row_id, asset_group, date) — schema error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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