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Save Files Analytics — Numeric Interval Filter + Trailing Mean Series
x402
Save Files Analytics — Numeric Interval Filter + 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 2026-11-06).
Filters save file records by a numeric range and computes a trailing moving average series for save_kb or write_ms fields, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Save files — Numeric interval filter + Trailing mean series: Numeric interval filter + Trailing mean series for supplied save files records (save_kb, write_ms). 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: (1) rows from the input dataset whose selected field (save_kb or write_ms) falls within the specified minimum–maximum interval, and (2) a trailing mean time series computed over the selected field using the specified window size. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Detecting save size bloat over time
“Here are 120 daily save file records for our RPG — filter to rows where save_kb is between 50 and 800, then give me a trailing mean with a window of 7 over save_kb so I can see if save sizes are trending upward.”
Monitoring write latency spikes in game areas
“I've got save logs for two game areas over the past three months — can you filter to write_ms values between 0 and 300, then compute a 10-row trailing mean on write_ms to smooth out any noisy spikes?”
Validating save performance after a patch
“After our latest patch, I want to check save performance — here are 80 save records, please filter to save_kb between 100 and 1000 and run a trailing mean with window size 4 on save_kb so I can compare before and after trends.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-13-126?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have game save file records with save_kb and write_ms metrics and need both a numeric range filter and a smoothed rolling average series in a single low-cost call. Ideal for game performance monitoring, patch comparison, and save size trend analysis on datasets up to 200 rows. Not suitable for external data lookups, predictions, or real-time streaming data.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds limit
- Window size larger than number of rows — trailing mean may produce sparse or empty results
- Invalid date format (not YYYY-MM-DD) — validation error
- Field value outside allowed numeric range — schema rejection
- Missing required fields (row_id, game_area, date, save_kb, write_ms) — validation error
- Minimum greater than maximum — may return empty filtered set
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer | |
| maximum | number | |
| minimum | number |
Tags
x402
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