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Backup Exercises — Adjacent Row Changes + Base-100 Series
x402
Backup Exercises — 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 2026-10-25).
Computes adjacent row-to-row changes and base-100 indexed series for up to 200 rows of backup exercise data (restore_minutes, restored_gb).
Price / call$0.01
Success—
StatusUnknown
How this service works
Backup exercises — Adjacent row changes + Base-100 series: Adjacent row changes + Base-100 series for supplied backup exercises records (restore_minutes, restored_gb). 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 backup exercise rows: (1) an adjacent row change report showing the delta in the selected field (restore_minutes or restored_gb) between each consecutive row, and (2) a base-100 indexed series anchoring the selected field's values relative to the specified base_index row. Both reports operate on the supplied data locally with no external lookups.
Example use cases
Backup speed trend over time
“I have 10 weekly backup exercise results with dates, group labels, restore_minutes, and restored_gb. Can you calculate how restore_minutes changed from one run to the next and also show me a base-100 indexed series starting from the first row?”
Comparing recovery times by control group
“I've got 50 backup exercise records split between group-a and group-b, each with a date, restore_minutes, and restored_gb. Please compute the adjacent row changes for restored_gb with base index at 0 so I can see how recovery volumes shifted across runs.”
Baseline-normalized backup performance report
“Can you take my 25-row backup exercise dataset — it has row IDs, dates, control groups, restore_minutes, and restored_gb — and produce both a row-to-row change report and a base-100 series for restore_minutes indexed from row 5?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-security-05-155?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular backup exercise records with restore_minutes or restored_gb metrics and need both a sequential row-change analysis and a base-100 normalized series in a single call. It is ideal for lightweight, local analytical computation on up to 200 rows without requiring an external analytics platform, database, or live data connection. Prefer alternatives if you need predictive modeling, real-time monitoring, or analysis of fields beyond the two supported metrics.
Side effects
- Fewer than 1 row supplied — minItems validation error
- More than 200 rows supplied — maxItems validation error
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- base_index out of range (>=200 or <0) — validation error
- Field value not in enum [restore_minutes, restored_gb] — validation error
- Null numeric values in key field may affect delta calculations
- Missing required row fields (row_id, control_group, date) — schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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