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Simulation Caches — Adjacent Row Changes + Base-100 Series
x402
Simulation Caches — Adjacent Row Changes + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).
Computes adjacent row-over-row changes and a base-100 indexed series for user-supplied simulation cache records (cache_gb, simulation_seconds) — two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Simulation caches — Adjacent row changes + Base-100 series: Adjacent row changes + Base-100 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 analytical reports for the supplied simulation cache rows: (1) an adjacent row changes report showing the delta of the selected field (cache_gb or simulation_seconds) between each consecutive row, and (2) a base-100 indexed series showing each row's value normalized relative to the row at base_index. Results are computed locally with no external lookup. Up to 200 rows supported per call.
Example use cases
Cache growth delta analysis
“I have daily simulation cache readings across two asset groups for October 2026 — can you compute the adjacent row-over-row changes in cache_gb for these 4 records and also give me a base-100 series starting from row 0? Row data: group-a 2026-10-01 cache_gb=10 sim_seconds=1, group-b 2026-10-02 cache_gb=20 sim_seconds=2, group-a 2026-10-03 cache_gb=15 sim_seconds=3, group-b 2026-10-04 cache_gb=30 sim_seconds=4.”
Simulation throughput baseline indexing
“For my simulation throughput data, I want to see how simulation_seconds evolved relative to the first row as a base-100 index — can you run both the adjacent changes report and the base-100 series on these records using simulation_seconds as the field, with base_index set to 0? Records: row-1 group-a 2026-10-01 cache_gb=10 sim_seconds=100, row-2 group-b 2026-10-02 cache_gb=20 sim_seconds=150, row-3 group-a 2026-10-03 cache_gb=15 sim_seconds=130.”
Mid-series baseline normalization
“I need a base-100 series for my cache_gb readings starting from row 2 as the baseline, plus the adjacent row differences — here are my 5 simulation records: row-1 group-a 2026-09-01 cache_gb=50 sim_seconds=5, row-2 group-b 2026-09-02 cache_gb=60 sim_seconds=6, row-3 group-a 2026-09-03 cache_gb=80 sim_seconds=8, row-4 group-b 2026-09-04 cache_gb=75 sim_seconds=7, row-5 group-a 2026-09-05 cache_gb=90 sim_seconds=9. Use base_index=2.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-08-155?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two specific analytical transformations — adjacent row-over-row deltas AND a base-100 normalized series — applied to simulation cache records (cache_gb or simulation_seconds) in a single low-cost call. It is ideal for time-series change analysis on small-to-medium datasets (up to 200 rows) where you supply the data directly and need fast, offline computation without live data lookup or prediction. Not suitable for real-time monitoring, external data retrieval, or analytical operations beyond these two report types.
Side effects
- Empty or missing rows array returns an error
- Rows exceeding the 200-item limit are rejected
- Invalid date format (non YYYY-MM-DD) causes validation failure
- base_index value exceeding the number of supplied rows triggers an out-of-bounds error
- Null values in the selected numeric field may produce undefined or skipped delta results
- Missing required row fields (row_id, asset_group, date) cause schema validation errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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