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Save Files — Record Quality Audit + String Normalisation + Keyed Dataset Comparison
x402
Save Files — Record Quality Audit + String Normalisation + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-03).
Audits record quality, normalises strings, and compares two keyed save-file datasets (save_kb, write_ms) across up to 200 rows, returning 3 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Save files — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison 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
Three independent reports: (1) a record quality audit flagging missing, null, or out-of-range values in save_kb and write_ms; (2) a string normalisation report for the game_area field; and (3) a keyed dataset comparison identifying row-level differences between the primary and secondary datasets matched on row_id.
Example use cases
Detecting save file data drift between patches
“I have two snapshots of save file metrics from before and after our last patch — can you compare them row by row using row_id as the key, audit for quality issues, and normalize the game_area labels? Primary set has 50 rows with save_kb and write_ms values, and so does the comparison set.”
Cleaning messy game area labels in save logs
“My save file logs have inconsistent game_area strings like 'Group-A', 'group a', 'GROUP_A' — can you normalize them and also run a quality audit on the save_kb and write_ms columns for up to 150 rows?”
QA check before merging save file datasets
“Before I merge these two save file record sets, can you run a keyed dataset comparison on them using row_id, flag any quality issues in save_kb and write_ms, and normalize the game_area strings? Each set has about 80 rows dated between 2026-10-01 and 2026-12-31.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-game-13-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — record quality auditing, string normalisation, and keyed cross-dataset comparison — on game save file records (save_kb, write_ms) in a single $0.01 call. Ideal for game developers, QA engineers, or data pipelines that need to validate and reconcile save file metrics across two dataset snapshots without any external lookups or live data fetching.
Side effects
- More than 200 rows submitted — request rejected with maxItems validation error
- Missing required fields (row_id, game_area, date, save_kb, write_ms) in any row — schema validation error
- Date field does not match YYYY-MM-DD pattern — validation error
- Empty rows array — minItems:1 constraint violation
- Numeric values outside allowed range (-1e12 to 1e12) for save_kb or write_ms — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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