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Save Files Analytics — Numeric Distribution + Base-100 Series
x402
Save Files Analytics — Numeric Distribution + 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 2026-10-30).
Computes numeric distribution statistics and a base-100 indexed time series for save file metrics (save_kb and write_ms) across up to 200 supplied game save records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Save files — Numeric distribution + Base-100 series: Numeric distribution + Base-100 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 for up to 200 supplied save file rows: (1) a numeric distribution report showing frequency buckets and statistical spread of the selected metric (save_kb or write_ms), and (2) a base-100 indexed time series anchored at the specified base_index row, showing relative change across all records. No external data is fetched — analysis is performed entirely on the supplied data.
Example use cases
Game save size trend analysis
“I have 50 game save records across two areas and I want to see a base-100 series indexed from my first row plus a full numeric distribution — all based on save_kb. Can you run that analysis for me? The records include dates from 2026-01-01 through 2026-02-19 with save_kb and write_ms values per row.”
Write time performance distribution
“Can you analyze the distribution of write_ms values across my game save data and also give me a base-100 indexed series starting from row 0? I have about 80 save records with dates, game areas, and write times I can provide.”
Comparing save metrics across game areas
“I want to understand how save file sizes are distributed across my different game areas. Run a numeric distribution and base-100 series on my 120 save file records using the save_kb field, with base_index set to 0, so I can see how each area compares.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-13-078?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular game save file records (up to 200 rows) with save size (save_kb) or write time (write_ms) metrics and need both a distribution breakdown and a base-100 indexed trend series in a single low-cost call. It is ideal for offline or batch analytical workflows where no live data lookup or external enrichment is required — all analysis is performed on the data you supply. Prefer this over general-purpose analytics tools when you specifically need the combination of numeric distribution and base-indexed series for game save performance data.
Side effects
- Fewer than 1 row supplied — minimum of 1 row required
- More than 200 rows submitted — maxItems limit exceeded
- Invalid date format (must match YYYY-MM-DD pattern)
- base_index out of range (must be 0–199 and within submitted row count)
- field value not one of the allowed enum values: save_kb or write_ms
- Missing required row fields: row_id, game_area, date, save_kb, or write_ms
- Null numeric values may affect distribution and indexing calculations
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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