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Save Files Analyzer — Record Quality Audit + Exact Row Deduplication + Trailing Mean Series
x402
Save Files Analyzer — Record Quality Audit + Exact Row Deduplication + 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).
Runs three analytical reports on game save-file metrics (save_kb, write_ms): a record quality audit, exact row deduplication, and a trailing moving-average series.
Price / call$0.01
Success—
StatusUnknown
How this service works
Save files — Record quality audit + Exact row deduplication + Trailing mean series: Record quality audit + Exact row deduplication + Trailing mean series for supplied save files records (save_kb, write_ms). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports: (1) a record quality audit identifying missing, null, or malformed values; (2) an exact row deduplication report flagging or removing identical rows; and (3) a trailing mean time series for the specified numeric field (save_kb or write_ms) computed with the given window size. All computed locally from the supplied rows with no external lookups.
Example use cases
Game save data quality check
“I have 50 rows of game save records with save_kb and write_ms values across different game areas. Can you audit them for quality issues, deduplicate any exact repeats, and compute a trailing mean with window 4 on save_kb?”
Write latency smoothing for performance review
“Run a trailing mean with window 3 on write_ms across my save file records so I can see the smoothed write latency trend — also flag any duplicate rows and give me a quality audit.”
Cleaning and summarizing save file metrics
“I've got up to 150 rows of save file data from different game areas. Please deduplicate exact rows, audit record quality for nulls or format issues, and give me a trailing mean series on save_kb with window size 5.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-13-216?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of game save-file performance data (save_kb and/or write_ms) and need all three of: a data quality audit, exact duplicate detection, and a rolling average series — in a single cheap $0.01 call. Prefer this over generic data tools when working specifically with save-file metrics structured with row_id, game_area, and date fields.
Side effects
- Fewer than 1 or more than 200 rows supplied — rejected at input validation
- date field not matching YYYY-MM-DD format — row rejected or flagged
- window size larger than number of rows — trailing mean may be sparse or empty
- null values in the target field — affect trailing mean calculations
- row_id or game_area exceeding 80 characters — truncation or rejection
- Payment failure — x402 micropayment not accepted
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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