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Save Files Duplicate Key Report + Trailing Mean Series
x402
Save Files Duplicate Key Report + 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 2026-10-30).
Analyzes game save file records to produce a duplicate key report and a trailing mean time series for save_kb or write_ms metrics, across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Save files — Duplicate key report + Trailing mean series: Duplicate key report + 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 independent reports: (1) a duplicate key report identifying rows with repeated key combinations, and (2) a trailing mean series showing rolling averages of the selected numeric field (save_kb or write_ms) over the specified window size, covering up to 200 input rows.
Example use cases
Duplicate save record audit
“I have a list of 120 game save log entries with row_id, game_area, date, save_kb, and write_ms. Can you scan them for any duplicate keys and also give me a trailing mean of save_kb using a window of 5?”
Write latency rolling average
“Here are 80 save file records from our game backend — can you run a duplicate key check on them and compute a rolling mean of write_ms with a window of 4 so I can see the smoothed latency trend?”
Game area save size trend analysis
“I want to analyze save file sizes across different game areas. I have 150 rows with dates and save_kb values — can you flag any duplicate row_id entries and compute a trailing mean of save_kb over a window of 10?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-13-061?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have game save file records and need both duplicate key detection and a trailing mean time series in a single $0.01 call. It is best suited for offline/batch analytical quality checks on provided data — not for live lookups, predictions, or external data retrieval. Prefer this over generic analytics tools when your data fits the save_kb/write_ms schema and you need both reports together economically.
Side effects
- Missing required fields (row_id, game_area, date, save_kb, write_ms) cause validation errors
- Fewer than 1 row or more than 200 rows triggers schema rejection
- Window size outside 2–200 range causes parameter error
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- Non-numeric values for save_kb or write_ms where numbers are required cause type errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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