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Simulation Caches — Trailing Mean Series + Adjacent Row Changes
x402
Simulation Caches — Trailing Mean Series + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-31).
Computes trailing moving-average series and adjacent-row delta changes for simulation cache metrics (cache_gb, simulation_seconds) supplied as row data, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Trailing mean series + Adjacent row changes: Trailing mean series + Adjacent row changes 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 analytical reports for the supplied rows: (1) a trailing mean series showing the rolling average of the chosen field over the specified window, and (2) adjacent row changes showing the delta between consecutive rows — both computed locally without external lookups or predictions.
Example use cases
Cache growth trend monitoring
“I have a week of daily simulation cache readings in GB across two asset groups — can you compute a trailing mean with window 3 and show me the row-by-row changes so I can spot growth trends in cache_gb?”
Simulation runtime delta analysis
“Analyze my simulation_seconds data for 10 rows across different asset groups — give me a rolling average with window 2 and the adjacent row differences so I can see where runtimes are jumping.”
Infrastructure capacity planning review
“I want to compare cache sizes day over day and see a smoothed trailing mean across my 50 simulation cache records — use cache_gb as the field and a window of 5 for the moving average.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-146?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have simulation cache tabular data (up to 200 rows) and need both a smoothed rolling average and row-over-row delta analysis in a single low-cost call ($0.01 USDC). Ideal for offline/batch analytical tasks on already-collected simulation metrics without needing live data, predictions, or external integrations.
Side effects
- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — rejected with maxItems error
- Window size larger than number of rows — may produce empty or partial trailing mean series
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Missing required row fields (row_id, date, cache_gb, simulation_seconds) — schema error
- Field enum value not 'cache_gb' or 'simulation_seconds' — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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